Identifying Protein-Calorie Malnutrition Workshop.

ERIC Educational Resources Information Center

Walker, Susan S.; Barker, Ellen M.

Instructional materials are provided for a workshop to enable participants to assist in identifying patients at risk with protein-calorie malnutrition and in corrrecting this nutritional deficiency. Representative topics are nutrients; protein, mineral, and vitamin sources, functions, and deficiency symptoms; malnutrition; nutritional deficiency…

An integrated molecular analysis of lung adenocarcinomas identifies potential therapeutic targets among TTF1-negative tumors including DNA repair proteins and Nrf2

PubMed Central

Cardnell, Robert J.G.; Behrens, Carmen; Diao, Lixia; Fan, YouHong; Tang, Ximing; Tong, Pan; John D., Minna; Mills, Gordon B.; Heymach, John V.; Wistuba, Ignacio I.; Wang, Jing; Byers., Lauren A.

2015-01-01

Purpose Thyroid transcription factor-1 (TTF1) immunohistochemistry (IHC) is used clinically to differentiate primary lung adenocarcinomas (LUAD) from squamous lung cancers and metastatic adenocarcinomas from other primary sites. However, a subset of LUAD (15-20%) does not express TTF1 and TTF1-negative patients have worse clinical outcomes. As there are no established targeted agents with activity in TTF1-negative LUAD, we performed an integrated molecular analysis to identify potential therapeutic targets. Experimental Design Using two clinical LUAD cohorts (274 tumors), one from our institution (PROSPECT) and the TCGA, we interrogated proteomic profiles (by reverse-phase protein array (RPPA)), gene expression, and mutational data. Drug response data from 74 cell lines were used to validate potential therapeutic agents. Results Strong correlations were observed between TTF1 IHC and TTF1 measurements by RPPA (Rho=0.57, p<0.001) and gene expression (NKX2-1, Rho=0.61, p<0.001). Established driver mutations (e.g. BRAF and EGFR) were associated with high TTF1 expression. In contrast, TTF1-negative LUAD had a higher frequency of inactivating KEAP1 mutations (p=0.001). Proteomic profiling identified increased expression of DNA repair proteins (e.g., Chk1 and the DNA repair score) and suppressed PI3K/MAPK signaling among TTF1-negative tumors, with differences in total proteins confirmed at the mRNA level. Cell line analysis showed drugs targeting DNA repair to be more active in TTF1-low cell lines. Conclusions Combined genomic and proteomic analyses demonstrated infrequent alteration of validated lung cancer targets (including the absence of BRAF mutations in TTF1-negative LUAD), but identified novel potential targets for TTF1-negative LUAD includingKEAP1/Nrf2 and DNA repair pathways. PMID:25878335

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PubMed

Sasse, Alexander; de Vries, Sjoerd J; Schindler, Christina E M; de Beauchêne, Isaure Chauvot; Zacharias, Martin

2017-01-01

Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol.

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI).

A coevolution analysis for identifying protein-protein interactions by Fourier transform

PubMed Central

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

Identifying Key Attributes for Protein Beverages.

PubMed

Oltman, A E; Lopetcharat, K; Bastian, E; Drake, M A

2015-06-01

This study identified key attributes of protein beverages and evaluated effects of priming on liking of protein beverages. An adaptive choice-based conjoint study was conducted along with Kano analysis to gain insight on protein beverage consumers (n = 432). Attributes evaluated included label claim, protein type, amount of protein, carbohydrates, sweeteners, and metabolic benefits. Utility scores for levels and importance scores for attributes were determined. Subsequently, two pairs of clear acidic whey protein beverages were manufactured that differed by age of protein source or the amount of whey protein per serving. Beverages were evaluated by 151 consumers on two occasions with or without priming statements. One priming statement declared "great flavor," the other priming statement declared 20 g protein per serving. A two way analysis of variance was applied to discern the role of each priming statement. The most important attribute for protein beverages was sweetener type, followed by amount of protein, followed by type of protein followed by label claim. Beverages with whey protein, naturally sweetened, reduced sugar and ≥15 g protein per serving were most desired. Three consumer clusters were identified, differentiated by their preferences for protein type, sweetener and amount of protein. Priming statements positively impacted concept liking (P < 0.05) but had no effect on overall liking (P > 0.05). Consistent with trained panel profiles of increased cardboard flavor with higher protein content, consumers liked beverages with 10 g protein more than beverages with 20 g protein (6.8 compared with 5.7, P < 0.05). Protein beverages must have desirable flavor for wide consumer appeal. © 2015 Institute of Food Technologists®

Use of Phage Display to Identify Novel Mineralocorticoid Receptor-Interacting Proteins

PubMed Central

Yang, Jun; Fuller, Peter J.; Morgan, James; Shibata, Hirotaka; McDonnell, Donald P.; Clyne, Colin D.

2014-01-01

The mineralocorticoid receptor (MR) plays a central role in salt and water homeostasis via the kidney; however, inappropriate activation of the MR in the heart can lead to heart failure. A selective MR modulator that antagonizes MR signaling in the heart but not the kidney would provide the cardiovascular protection of current MR antagonists but allow for normal electrolyte balance. The development of such a pharmaceutical requires an understanding of coregulators and their tissue-selective interactions with the MR, which is currently limited by the small repertoire of MR coregulators described in the literature. To identify potential novel MR coregulators, we used T7 phage display to screen tissue-selective cDNA libraries for MR-interacting proteins. Thirty MR binding peptides were identified, from which three were chosen for further characterization based on their nuclear localization and their interaction with other MR-interacting proteins or, in the case of x-ray repair cross-complementing protein 6, its known status as an androgen receptor coregulator. Eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 modulated MR-mediated transcription in a ligand-, cell- and/or promoter-specific manner and colocalized with the MR upon agonist treatment when imaged using immunofluorescence microscopy. These results highlight the utility of phage display for rapid and sensitive screening of MR binding proteins and suggest that eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 may be potential MR coactivators whose activity is dependent on the ligand, cellular context, and target gene promoter. PMID:25000480

Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses.

PubMed

Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

2016-01-01

Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.

Identifying protein biomarkers in predicting disease severity of dengue virus infection using immune-related protein microarray.

PubMed

Soe, Hui Jen; Yong, Yean K; Al-Obaidi, Mazen M Jamil; Raju, Chandramathi Samudi; Gudimella, Ranganath; Manikam, Rishya; Sekaran, Shamala Devi

2018-02-01

Dengue virus is one of the most widespread flaviviruses that re-emerged throughout recent decades. The progression from mild dengue to severe dengue (SD) with the complications such as vascular leakage and hemorrhage increases the fatality rate of dengue. The pathophysiology of SD is not entirely clear. To investigate potential biomarkers that are suggestive of pathogenesis of SD, a small panel of serum samples selected from 1 healthy individual, 2 dengue patients without warning signs (DWS-), 2 dengue patients with warning signs (DWS+), and 5 patients with SD were subjected to a pilot analysis using Sengenics Immunome protein array. The overall fold changes of protein expressions and clustering heat map revealed that PFKFB4, TPM1, PDCL3, and PTPN20A were elevated among patients with SD. Differential expression analysis identified that 29 proteins were differentially elevated greater than 2-fold in SD groups than DWS- and DWS+. From the 29 candidate proteins, pathways enrichment analysis also identified insulin signaling and cytoskeleton pathways were involved in SD, suggesting that the insulin pathway may play a pivotal role in the pathogenesis of SD.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Novel isoprenylated proteins identified by an expression library screen.

PubMed

Biermann, B J; Morehead, T A; Tate, S E; Price, J R; Randall, S K; Crowell, D N

1994-10-14

Isoprenylated proteins are involved in eukaryotic cell growth and signal transduction. The protein determinant for prenylation is a short carboxyl-terminal motif containing a cysteine, to which the isoprenoid is covalently attached via thioether linkage. To date, isoprenylated proteins have almost all been identified by demonstrating the attachment of an isoprenoid to previously known proteins. Thus, many isoprenylated proteins probably remain undiscovered. To identify novel isoprenylated proteins for subsequent biochemical study, colony blots of a Glycine max cDNA expression library were [3H]farnesyl-labeled in vitro. Proteins identified by this screen contained several different carboxyl termini that conform to consensus farnesylation motifs. These proteins included known farnesylated proteins (DnaJ homologs) and several novel proteins, two of which contained six or more tandem repeats of a hexapeptide having the consensus sequence (E/G)(G/P)EK(P/K)K. Thus, plants contain a diverse array of genes encoding farnesylated proteins, and our results indicate that fundamental differences in the identities of farnesylated proteins may exist between plants and other eukaryotes. Expression library screening by direct labeling can be adapted to identify isoprenylated proteins from other organisms, as well as proteins with other post-translational modifications.

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer.

PubMed

Drabik, Anna; Bodzon-Kulakowska, Anna; Suder, Piotr; Silberring, Jerzy; Kulig, Jan; Sierzega, Marek

2017-04-07

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

A Discontinuous Potential Model for Protein-Protein Interactions.

PubMed

Shao, Qing; Hall, Carol K

2016-01-01

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.

2009-01-01

Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435

Proteomic profiling of human plasma exosomes identifies PPAR{gamma} as an exosome-associated protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Looze, Christopher; Yui, David; Leung, Lester

Exosomes are nanovesicles that are released from cells as a mechanism of cell-free intercellular communication. Only a limited number of proteins have been identified from the plasma exosome proteome. Here, we developed a multi-step fractionation scheme incorporating gel exclusion chromatography, rate zonal centrifugation through continuous sucrose gradients, and high-speed centrifugation to purify exosomes from human plasma. Exosome-associated proteins were separated by SDS-PAGE and 66 proteins were identified by LC-MS/MS, which included both cellular and extracellular proteins. Furthermore, we identified and characterized peroxisome proliferator-activated receptor-{gamma} (PPAR{gamma}), a nuclear receptor that regulates adipocyte differentiation and proliferation, as well as immune and inflammatorymore » cell functions, as a novel component of plasma-derived exosomes. Given the important role of exosomes as intercellular messengers, the discovery of PPAR{gamma} as a component of human plasma exosomes identifies a potential new pathway for the paracrine transfer of nuclear receptors.« less

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

PubMed Central

Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases. PMID:27191267

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE PAGES

Shatsky, Maxim; Dong, Ming; Liu, Haichuan; ...

2016-04-20

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shatsky, Maxim; Dong, Ming; Liu, Haichuan

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network.

PubMed

Uddin, Reaz; Jamil, Faiza

2018-06-01

Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Therapeutic Potential for Marine Skeletal Proteins in Bone Regeneration

PubMed Central

Green, David W.; Padula, Matthew P.; Santos, Jerran; Chou, Joshua; Milthorpe, Bruce; Ben-Nissan, Besim

2013-01-01

A vital ingredient for engineering bone tissue, in the culture dish, is the use of recombinant matrix and growth proteins to help accelerate the growth of cultivated tissues into clinically acceptable quantities. The skeletal organic matrices of calcifying marine invertebrates are an untouched potential source of such growth inducing proteins. They have the advantage of being ready-made and retain the native state of the original protein. Striking evidence shows that skeleton building bone morphogenic protein-2/4 (BMP) and transforming growth factor beta (TGF-β) exist within various marine invertebrates such as, corals. Best practice mariculture and the latest innovations in long-term marine invertebrate cell cultivation can be implemented to ensure that these proteins are produced sustainably and supplied continuously. This also guarantees that coral reef habitats are not damaged during the collection of specimens. Potential proteins for bone repair, either extracted from the skeleton or derived from cultivated tissues, can be identified, evaluated and retrieved using chromatography, cell assays and proteomic methods. Due to the current evidence for bone matrix protein analogues in marine invertebrates, together with the methods established for their production and retrieval there is a genuine prospect that they can be used to regenerate living bone for potential clinical use. PMID:23574983

Interaction of Proteins Identified in Human Thyroid Cells

PubMed Central

Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

2013-01-01

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

New insights into potential functions for the protein 4.1superfamily of proteins in kidney epithelium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calinisan, Venice; Gravem, Dana; Chen, Ray Ping-Hsu

2005-06-17

Members of the protein 4.1 family of adapter proteins are expressed in a broad panel of tissues including various epithelia where they likely play an important role in maintenance of cell architecture and polarity and in control of cell proliferation. We have recently characterized the structure and distribution of three members of the protein 4.1 family, 4.1B, 4.1R and 4.1N, in mouse kidney. We describe here binding partners for renal 4.1 proteins, identified through the screening of a rat kidney yeast two-hybrid system cDNA library. The identification of putative protein 4.1-based complexes enables us to envision potential functions for 4.1more » proteins in kidney: organization of signaling complexes, response to osmotic stress, protein trafficking, and control of cell proliferation. We discuss the relevance of these protein 4.1-based interactions in kidney physio-pathology in the context of their previously identified functions in other cells and tissues. Specifically, we will focus on renal 4.1 protein interactions with beta amyloid precursor protein (beta-APP), 14-3-3 proteins, and the cell swelling-activated chloride channel pICln. We also discuss the functional relevance of another member of the protein 4.1 superfamily, ezrin, in kidney physiopathology.« less

IBT-based quantitative proteomics identifies potential regulatory proteins involved in pigmentation of purple sea cucumber, Apostichopus japonicus.

PubMed

Xing, Lili; Sun, Lina; Liu, Shilin; Li, Xiaoni; Zhang, Libin; Yang, Hongsheng

2017-09-01

Sea cucumbers are an important economic species and exhibit high yield value among aquaculture animals. Purple sea cucumbers are very rare and beautiful and have stable hereditary patterns. In this study, isobaric tags (IBT) were first used to reveal the molecular mechanism of pigmentation in the body wall of the purple sea cucumber. We analyzed the proteomes of purple sea cucumber in early pigmentation stage (Pa), mid pigmentation stage (Pb) and late pigmentation stage (Pc), resulting in the identification of 5580 proteins, including 1099 differentially expressed proteins in Pb: Pa and 339 differentially expressed proteins in Pc: Pb. GO and KEGG analyses revealed possible differentially expressed proteins, including"melanogenesis", "melanosome", "melanoma", "pigment-biosynthetic process", "Epidermis development", "Ras-signaling pathway", "Wnt-signaling pathway", "response to UV light", and "tyrosine metabolism", involved in pigment synthesis and regulation in purple sea cucumbers. The large number of differentially expressed proteins identified here should be highly useful in further elucidating the mechanisms underlying pigmentation in sea cucumbers. Furthermore, these results may also provide the base for further identification of proteins involved in resistance mechanisms against melanoma, albinism, UV damage, and other diseases in sea cucumbers. Copyright © 2017. Published by Elsevier Inc.

Potential Interference of Protein-Protein Interactions by Graphyne.

PubMed

Luan, Binquan; Huynh, Tien; Zhou, Ruhong

2016-03-10

Graphyne has attracted tremendous attention recently due to its many potentially superior properties relative to those of graphene. Although extensive efforts have been devoted to explore the applicability of graphyne as an alternative nanomaterial for state-of-the-art nanotechnology (including biomedical applications), knowledge regarding its possible adverse effects to biological cells is still lacking. Here, using large-scale all-atom molecular dynamics simulations, we investigate the potential toxicity of graphyne by interfering a protein-protein interaction (ppI). We found that graphyne could indeed disrupt the ppIs by cutting through the protein-protein interface and separating the protein complex into noncontacting ones, due to graphyne's dispersive and hydrophobic interaction with the hydrophobic residues residing at the dimer interface. Our results help to elucidate the mechanism of interaction between graphyne and ppI networks within a biological cell and provide insights for its hazard reduction.

A lanthipeptide library used to identify a protein-protein interaction inhibitor.

PubMed

Yang, Xiao; Lennard, Katherine R; He, Chang; Walker, Mark C; Ball, Andrew T; Doigneaux, Cyrielle; Tavassoli, Ali; van der Donk, Wilfred A

2018-04-01

In this article we describe the production and screening of a genetically encoded library of 10 6 lanthipeptides in Escherichia coli using the substrate-tolerant lanthipeptide synthetase ProcM. This plasmid-encoded library was combined with a bacterial reverse two-hybrid system for the interaction of the HIV p6 protein with the UEV domain of the human TSG101 protein, which is a critical protein-protein interaction for HIV budding from infected cells. Using this approach, we identified an inhibitor of this interaction from the lanthipeptide library, whose activity was verified in vitro and in cell-based virus-like particle-budding assays. Given the variety of lanthipeptide backbone scaffolds that may be produced with ProcM, this method may be used for the generation of genetically encoded libraries of natural product-like lanthipeptides containing substantial structural diversity. Such libraries may be combined with any cell-based assay to identify lanthipeptides with new biological activities.

Peptides identified in soybean protein increase plasma cholesterol in mice on hypercholesterolemic diets

USDA-ARS?s Scientific Manuscript database

The in vitro micellar cholesterol displacement assay has been used to identify peptides that may potentially reduce cholesterol in vivo. We tested two of these peptides, LPYPR and WGAPSI, derived from soybean protein (SP) that have been reported to displace cholesterol from micelles by feeding them...

Whole Protein Native Fitness Potentials

NASA Astrophysics Data System (ADS)

Faraggi, Eshel; Kloczkowski, Andrzej

2013-03-01

Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

Potential disruption of protein-protein interactions by graphene oxide

NASA Astrophysics Data System (ADS)

Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong

2016-06-01

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide.

PubMed

Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong

2016-06-14

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Mei; Kang, Hongsuk; Luan, Binquan

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions andmore » eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.« less

SELDI-TOF-MS ProteinChip array profiling of T-cell clones propagated in long-term culture identifies human profilin-1 as a potential bio-marker of immunosenescence.

PubMed

Mazzatti, Dawn J; Pawelec, Graham; Longdin, Robin; Powell, Jonathan R; Forsey, Rosalyn J

2007-06-05

The adaptive immune response requires waves of T-cell clonal expansion on contact with pathogen and elimination after clearance of the source of antigen. However, lifelong persistent infections with common viruses cause chronic antigenic stimulation which takes its toll on adaptive immunity in late life. Chronic antigenic stress results in deregulation of the T-cell response and accumulation of anergic cells. Longitudinal studies of the elderly show that this impacts on survival. Identifying the nature of the defects in chronically-stimulated T-cells and protein bio-markers of these dysfunctional cells would help to understand age-associated compromised T-cell function (immunosenescence) and facilitate the development of targeted intervention strategies.The purpose of this work was to use surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to analyse proteins associated with T-cell senescence in order to identify potential bio-markers. Clonal populations of T-cells isolated from elderly octogenarian and centenarian donors were grown in vitro until senescence, and early passage and late passage (pre-senescent) cells were analysed using SELDI-TOF-MS ProteinChip arrays. Discriminant analysis identified several protein or peptide peaks in the region of 14.5-16.5 kDa that were associated with T-cell clone senescence. Human profilin-1, a ubiquitous protein associated with actin remodelling and cellular motility was unambiguously identified. Altered expression of profilin-1 in senescent T-cell clones was confirmed by Western blot analysis. Due to the proposed roles of profilin-1 in cellular survival, cytoskeleton remodelling, motility, and proliferation, it is hypothesised that differential expression of profilin-1 in ageing may contribute directly to immunosenescence.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

Genome-wide analysis of gene expression and protein secretion of Babesia canis during virulent infection identifies potential pathogenicity factors.

PubMed

Eichenberger, Ramon M; Ramakrishnan, Chandra; Russo, Giancarlo; Deplazes, Peter; Hehl, Adrian B

2017-06-13

Infections of dogs with virulent strains of Babesia canis are characterized by rapid onset and high mortality, comparable to complicated human malaria. As in other apicomplexan parasites, most Babesia virulence factors responsible for survival and pathogenicity are secreted to the host cell surface and beyond where they remodel and biochemically modify the infected cell interacting with host proteins in a very specific manner. Here, we investigated factors secreted by B. canis during acute infections in dogs and report on in silico predictions and experimental analysis of the parasite's exportome. As a backdrop, we generated a fully annotated B. canis genome sequence of a virulent Hungarian field isolate (strain BcH-CHIPZ) underpinned by extensive genome-wide RNA-seq analysis. We find evidence for conserved factors in apicomplexan hemoparasites involved in immune-evasion (e.g. VESA-protein family), proteins secreted across the iRBC membrane into the host bloodstream (e.g. SA- and Bc28 protein families), potential moonlighting proteins (e.g. profilin and histones), and uncharacterized antigens present during acute crisis in dogs. The combined data provides a first predicted and partially validated set of potential virulence factors exported during fatal infections, which can be exploited for urgently needed innovative intervention strategies aimed at facilitating diagnosis and management of canine babesiosis.

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

PubMed Central

Deming, Yuetiva; Xia, Jian; Cai, Yefei; Lord, Jenny; Del-Aguila, Jorge L.; Fernandez, Maria Victoria; Carrell, David; Black, Kathleen; Budde, John; Ma, ShengMei; Saef, Benjamin; Howells, Bill; Bertelsen, Sarah; Bailey, Matthew; Ridge, Perry G.; Hefti, Franz; Fillit, Howard; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Carrillo, Maria; Fleisher, Adam; Reeder, Stephanie; Trncic, Nadira; Burke, Anna; Tariot, Pierre; Reiman, Eric M.; Chen, Kewei; Sabbagh, Marwan N.; Beiden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Green, Robert C.; Marshall, Gad; Johnson, Keith A.; Sperling, Reisa A.; Snyder, Peter; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Bernick, Charles; Munic, Donna; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Relkin, Norman; Chaing, Gloria; Ravdin, Lisa; Paul, Steven; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Friedl, Karl; Murali Doraiswamy, P.; Petrella, Jeffrey R.; Borges-Neto, Salvador; James, Olga; Wong, Terence; Coleman, Edward; Schwartz, Adam; Cellar, Janet S.; Levey, Allan L.; Lah, James J.; Behan, Kelly; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Farlow, Martin R.; Saykin, Andrew J.; Foroud, Tatiana M.; Shen, Li; Faber, Kelly; Kim, Sungeun; Nho, Kwangsik; Marie Hake, Ann; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Petersen, Ronald; Jack, Clifford R.; Bernstein, Matthew; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Chertkow, Howard; Hosein, Chris; Mintzer, Jacob; Spicer, Kenneth; Bachman, David; Grossman, Hillel; Mitsis, Effie; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Potter, William; Buckholtz, Neil; Hsiao, John; Kittur, Smita; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J; Glodzik, Lidia; De Santi, Susan; Johnson, Nancy; Chuang-Kuo; Kerwin, Diana; Bonakdarpour, Borna; Weintraub, Sandra; Grafman, Jordan; Lipowski, Kristine; Mesulam, Marek-Marsel; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Borrie, Michael; Lee, T-Y; Bartha, Rob; Martinez, Walter; Villena, Teresa; Sadowsky, Carl; Khachaturian, Zaven; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Frank, Richard; Fleischman, Debra; Arfanakis, Konstantinos; Shah, Raj C.; deToledo-Morrell, Leyla; Sorensen, Greg; Finger, Elizabeth; Pasternack, Stephen; Rachinsky, Irina; Drost, Dick; Rogers, John; Kertesz, Andrew; Furst, Ansgar J.; Chad, Stevan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Mudge, Benita; Assaly, Michele; Fox, Nick; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Ekstam Smith, Karen; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Natelson Love, Marissa; DeCarli, Charles; Carmichael, Owen; Olichney, John; Maillard, Pauline; Fletcher, Evan; Nguyen, Dana; Preda, Andrian; Potkin, Steven; Mulnard, Ruth A.; Thai, Gaby; McAdams-Ortiz, Catherine; Landau, Susan; Jagust, William; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Thompson, Paul; Donohue, Michael; Thomas, Ronald G.; Walter, Sarah; Gessert, Devon; Brewer, James; Vanderswag, Helen; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Aisen, Paul; Davis, Melissa; Morrison, Rosemary; Harvey, Danielle; Thal, Lean; Beckett, Laurel; Neylan, Thomas; Finley, Shannon; Weiner, Michael W.; Hayes, Jacqueline; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Massoglia, Dino; Brawman-Mentzer, Olga; Schuff, Norbert; Smith, Charles D.; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Koeppe, Robert A.; Lord, Joanne L.; Heidebrink, Judith L.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Trojanowki, John Q.; Shaw, Leslie M.; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Foster, Norm; Montine, Tom; Fruehling, J. Jay; Harding, Sandra; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Petrie, Eric C.; Peskind, Elaine; Li, Gail; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Smith, Amanda; Ashok Raj, Balebail; Fargher, Kristin; Kuller, Lew; Mathis, Chet; Ann Oakley, Mary; Lopez, Oscar L.; Simpson, Donna M.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Cairns, Nigel J.; Raichle, Marc; Morris, John C.; Householder, Erin; Taylor-Reinwald, Lisa; Holtzman, David; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Varma, Pradeep; MacAvoy, Martha G.; Carson, Richard E.; van Dyck, Christopher H.; Davies, Peter; Holtzman, David; Morris, John C.; Bales, Kelly; Pickering, Eve H.; Lee, Jin-Moo; Heitsch, Laura; Kauwe, John; Goate, Alison; Piccio, Laura; Cruchaga, Carlos

2016-01-01

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes, and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels, and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r, and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects, and complex disease associations in the same locus.

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

PubMed Central

Ren, Jun; Zhou, Wei; Wang, Jianxin

2014-01-01

Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes. PMID:25143945

Identifying paths of allosteric communication in the protein BirA through simulations

NASA Astrophysics Data System (ADS)

Custer, Gregory; Beckett, Dorothy; Matysiak, Silvina

Biotin ligase/repressor (BirA) is a bifunctional enzyme which adenylates biotin and transfers the product, biotinyl-5'-AMP (bio-5'-AMP) to biotin carboxyl carrier protein (BCCP). In the absence of BCCP, bio-5'-AMP promotes the dimerization of BirA. In dimer form, the BirA.bio-5'-AMP complex is able to bind to the biotin operator and prevents further synthesis of biotin. The bio-5'-AMP binds away from the dimer interface, so it is acting as an allosteric activator. We perform all-atom molecular dynamics simulations with BirA to look at fluctuations within the protein at equilibrium. We simulate apoBirA, liganded BirA, as well as two mutants, M211A and V219A. In agreement with experimental observations, several loops of the protein become stabilized for the liganded BirA when compared to the apo protein. In addition, changes in the dimer interface are observed for the M211A and V219A mutations, which are located in the ligand binding region. Using inter-residue correlation coefficients and pair energies a communication network through the protein is constructed. With this network we have identified paths which have the potential to be important in allosteric activation of BirA. These paths and the methods we use to identify them will be presented.

Improvements in the Protein Identifier Cross-Reference service.

PubMed

Wein, Samuel P; Côté, Richard G; Dumousseau, Marine; Reisinger, Florian; Hermjakob, Henning; Vizcaíno, Juan A

2012-07-01

The Protein Identifier Cross-Reference (PICR) service is a tool that allows users to map protein identifiers, protein sequences and gene identifiers across over 100 different source databases. PICR takes input through an interactive website as well as Representational State Transfer (REST) and Simple Object Access Protocol (SOAP) services. It returns the results as HTML pages, XLS and CSV files. It has been in production since 2007 and has been recently enhanced to add new functionality and increase the number of databases it covers. Protein subsequences can be Basic Local Alignment Search Tool (BLAST) against the UniProt Knowledgebase (UniProtKB) to provide an entry point to the standard PICR mapping algorithm. In addition, gene identifiers from UniProtKB and Ensembl can now be submitted as input or mapped to as output from PICR. We have also implemented a 'best-guess' mapping algorithm for UniProt. In this article, we describe the usefulness of PICR, how these changes have been implemented, and the corresponding additions to the web services. Finally, we explain that the number of source databases covered by PICR has increased from the initial 73 to the current 102. New resources include several new species-specific Ensembl databases as well as the Ensembl Genome ones. PICR can be accessed at http://www.ebi.ac.uk/Tools/picr/.

Potential hydrophobic protein markers of breast cancer in Malaysian Chinese, Malay and Indian patients.

PubMed

Liang, Seng; Singh, Manjit; Gam, Lay-Harn

Breast cancer is a leading cause of worldwide mortality in females. In Malaysia, breast cancer is the most commonly diagnosed cancer in women. Of these, the Chinese had the most number of breast cancer cases, followed by the Indian and the Malay. The most common type of breast cancer is infiltrating ductal carcinoma (IDC). A proteomic approach was used to identify protein profile changes in cancerous tissues compared with the normal tissues, the tissues were collected from patients of three different ethnicities, i.e. Chinese, Malay and Indian. Ten differentially expressed hydrophobic proteins were identified. We had evaluated the potential of these proteins as biomarker for infiltrating ducal carcinoma (IDC) and the ethnic-specific expression of these proteins was also determined. The data showed that peroxiredoxin-2, heat shock protein 60, protein disulfide isomerase and calreticulin may serve as ethnic-related potential markers for either one or combination of Chinese, Malay and Indian cohorts as their expression levels were significantly high in the cancerous tissues compared to the normal tissues in the ethnic group tested.

Identifying potential selective fluorescent probes for cancer-associated protein carbonic anhydrase IX using a computational approach.

PubMed

Kamstra, Rhiannon L; Floriano, Wely B

2014-11-01

Carbonic anhydrase IX (CAIX) is a biomarker for tumor hypoxia. Fluorescent inhibitors of CAIX have been used to study hypoxic tumor cell lines. However, these inhibitor-based fluorescent probes may have a therapeutic effect that is not appropriate for monitoring treatment efficacy. In the search for novel fluorescent probes that are not based on known inhibitors, a database of 20,860 fluorescent compounds was virtually screened against CAIX using hierarchical virtual ligand screening (HierVLS). The screening database contained 14,862 compounds tagged with the ATTO680 fluorophore plus an additional 5998 intrinsically fluorescent compounds. Overall ranking of compounds to identify hit molecular probe candidates utilized a principal component analysis (PCA) approach. Four potential binding sites, including the catalytic site, were identified within the structure of the protein and targeted for virtual screening. Available sequence information for 23 carbonic anhydrase isoforms was used to prioritize the four sites based on the estimated "uniqueness" of each site in CAIX relative to the other isoforms. A database of 32 known inhibitors and 478 decoy compounds was used to validate the methodology. A receiver-operating characteristic (ROC) analysis using the first principal component (PC1) as predictive score for the validation database yielded an area under the curve (AUC) of 0.92. AUC is interpreted as the probability that a binder will have a better score than a non-binder. The use of first component analysis of binding energies for multiple sites is a novel approach for hit selection. The very high prediction power for this approach increases confidence in the outcome from the fluorescent library screening. Ten of the top scoring candidates for isoform-selective putative binding sites are suggested for future testing as fluorescent molecular probe candidates. Copyright © 2014 Elsevier Inc. All rights reserved.

Orientation-dependent potential of mean force for protein folding

NASA Astrophysics Data System (ADS)

Mukherjee, Arnab; Bhimalapuram, Prabhakar; Bagchi, Biman

2005-07-01

We present a solvent-implicit minimalistic model potential among the amino acid residues of proteins, obtained by using the known native structures [deposited in the Protein Data Bank (PDB)]. In this model, the amino acid side chains are represented by a single ellipsoidal site, defined by the group of atoms about the center of mass of the side chain. These ellipsoidal sites interact with other sites through an orientation-dependent interaction potential which we construct in the following fashion. First, the site-site potential of mean force (PMF) between heavy atoms is calculated [following F. Melo and E. Feytsman, J. Mol. Biol. 267, 207 (1997)] from statistics of their distance separation obtained from crystal structures. These site-site potentials are then used to calculate the distance and the orientation-dependent potential between side chains of all the amino acid residues (AAR). The distance and orientation dependencies show several interesting results. For example, we find that the PMF between two hydrophobic AARs, such as phenylalanine, is strongly attractive at short distances (after the obvious repulsive region at very short separation) and is characterized by a deep minimum, for specific orientations. For the interaction between two hydrophilic AARs, such a deep minimum is absent and in addition, the potential interestingly reveals the combined effect of polar (charge) and hydrophobic interactions among some of these AARs. The effectiveness of our potential has been tested by calculating the Z-scores for a large set of proteins. The calculated Z-scores show high negative values for most of them, signifying the success of the potential to identify the native structure from among a large number of its decoy states.

A Fluorescent Live Imaging Screening Assay Based on Translocation Criteria Identifies Novel Cytoplasmic Proteins Implicated in G Protein-coupled Receptor Signaling Pathways*

PubMed Central

Lecat, Sandra; Matthes, Hans W.D.; Pepperkok, Rainer; Simpson, Jeremy C.; Galzi, Jean-Luc

2015-01-01

Several cytoplasmic proteins that are involved in G protein-coupled receptor signaling cascades are known to translocate to the plasma membrane upon receptor activation, such as beta-arrestin2. Based on this example and in order to identify new cytoplasmic proteins implicated in the ON-and-OFF cycle of G protein-coupled receptor, a live-imaging screen of fluorescently labeled cytoplasmic proteins was performed using translocation criteria. The screening of 193 fluorescently tagged human proteins identified eight proteins that responded to activation of the tachykinin NK2 receptor by a change in their intracellular localization. Previously we have presented the functional characterization of one of these proteins, REDD1, that translocates to the plasma membrane. Here we report the results of the entire screening. The process of cell activation was recorded on videos at different time points and all the videos can be visualized on a dedicated website. The proteins BAIAP3 and BIN1, partially translocated to the plasma membrane upon activation of NK2 receptors. Proteins ARHGAP12 and PKM2 translocated toward membrane blebs. Three proteins that associate with the cytoskeleton were of particular interest : PLEKHH2 rearranged from individual dots located near the cell-substrate adhesion surface into lines of dots. The speriolin-like protein, SPATC1L, redistributed to cell-cell junctions. The Chloride intracellular Channel protein, CLIC2, translocated from actin-enriched plasma membrane bundles to cell-cell junctions upon activation of NK2 receptors. CLIC2, and one of its close paralogs, CLIC4, were further shown to respond with the same translocation pattern to muscarinic M3 and lysophosphatidic LPA receptors. This screen allowed us to identify potential actors in signaling pathways downstream of G protein-coupled receptors and could be scaled-up for high-content screening. PMID:25759509

A Fluorescent Live Imaging Screening Assay Based on Translocation Criteria Identifies Novel Cytoplasmic Proteins Implicated in G Protein-coupled Receptor Signaling Pathways.

PubMed

Lecat, Sandra; Matthes, Hans W D; Pepperkok, Rainer; Simpson, Jeremy C; Galzi, Jean-Luc

2015-05-01

Several cytoplasmic proteins that are involved in G protein-coupled receptor signaling cascades are known to translocate to the plasma membrane upon receptor activation, such as beta-arrestin2. Based on this example and in order to identify new cytoplasmic proteins implicated in the ON-and-OFF cycle of G protein-coupled receptor, a live-imaging screen of fluorescently labeled cytoplasmic proteins was performed using translocation criteria. The screening of 193 fluorescently tagged human proteins identified eight proteins that responded to activation of the tachykinin NK2 receptor by a change in their intracellular localization. Previously we have presented the functional characterization of one of these proteins, REDD1, that translocates to the plasma membrane. Here we report the results of the entire screening. The process of cell activation was recorded on videos at different time points and all the videos can be visualized on a dedicated website. The proteins BAIAP3 and BIN1, partially translocated to the plasma membrane upon activation of NK2 receptors. Proteins ARHGAP12 and PKM2 translocated toward membrane blebs. Three proteins that associate with the cytoskeleton were of particular interest : PLEKHH2 rearranged from individual dots located near the cell-substrate adhesion surface into lines of dots. The speriolin-like protein, SPATC1L, redistributed to cell-cell junctions. The Chloride intracellular Channel protein, CLIC2, translocated from actin-enriched plasma membrane bundles to cell-cell junctions upon activation of NK2 receptors. CLIC2, and one of its close paralogs, CLIC4, were further shown to respond with the same translocation pattern to muscarinic M3 and lysophosphatidic LPA receptors. This screen allowed us to identify potential actors in signaling pathways downstream of G protein-coupled receptors and could be scaled-up for high-content screening. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast.

PubMed

Huang, Mingtao; Bai, Yunpeng; Sjostrom, Staffan L; Hallström, Björn M; Liu, Zihe; Petranovic, Dina; Uhlén, Mathias; Joensson, Haakan N; Andersson-Svahn, Helene; Nielsen, Jens

2015-08-25

There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used high-throughput microfluidics for the screening of yeast libraries, generated by UV mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant α-amylase. Efficient secretion was genetically stable in the selected clones. We performed whole-genome sequencing of the eight clones and identified 330 mutations in total. Gene ontology analysis of mutated genes revealed many biological processes, including some that have not been identified before in the context of protein secretion. Mutated genes identified in this study can be potentially used for reverse metabolic engineering, with the objective to construct efficient cell factories for protein secretion. The combined use of microfluidics screening and whole-genome sequencing to map the mutations associated with the improved phenotype can easily be adapted for other products and cell types to identify novel engineering targets, and this approach could broadly facilitate design of novel cell factories.

An ensemble framework for identifying essential proteins.

PubMed

Zhang, Xue; Xiao, Wangxin; Acencio, Marcio Luis; Lemke, Ney; Wang, Xujing

2016-08-25

Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, and the number of common predicted essential proteins by different methods is very small. In this paper, an ensemble framework is proposed which integrates gene expression data and protein-protein interaction networks (PINs). It aims to improve the prediction accuracy of basic centrality measures. The idea behind this ensemble framework is that different protein-protein interactions (PPIs) may show different contributions to protein essentiality. Five standard centrality measures (degree centrality, betweenness centrality, closeness centrality, eigenvector centrality, and subgraph centrality) are integrated into the ensemble framework respectively. We evaluated the performance of the proposed ensemble framework using yeast PINs and gene expression data. The results show that it can considerably improve the prediction accuracy of the five centrality measures individually. It can also remarkably increase the number of common predicted essential proteins among those predicted by each centrality measure individually and enable each centrality measure to find more low-degree essential proteins. This paper demonstrates that it is valuable to differentiate the contributions of different PPIs for identifying essential proteins based on network topological characteristics. The proposed ensemble framework is a successful paradigm to this end.

Current codex guidelines for assessment of potential protein allergenicity.

PubMed

Ladics, G S

2008-10-01

A rigorous safety assessment process exists for GM crops. It includes evaluation of the introduced protein as well as the crop containing such protein with the goal of demonstrating the GM crop is "as-safe-as" non-transgenic crops in the food supply. One of the major issues for GM crops is the assessment of the expressed protein for allergenic potential. Currently, no single factor is recognized as an identifier for protein allergenicity. Therefore, a weight-of-evidence approach, which takes into account a variety of factors and approaches for an overall assessment of allergenic potential, is conducted [Codex Alimentarious Commission, 2003. Alinorm 03/34: Joint FAO/WHO Food Standard Programme, Codex Alimentarious Commission, Twenty-Fifth Session, Rome, Italy, 30 June-5 July, 2003. Appendix III, Guideline for the conduct of food safety assessment of foods derived from recombinant-DNA plants, and Appendix IV, Annex on the assessment of possible allergenicity, pp. 47-60]. This assessment is based on what is known about allergens, including the history of exposure and safety of the gene(s) source; protein structure (e.g., amino acid sequence identity to human allergens); stability to pepsin digestion in vitro [Thomas, K. et al., 2004. A multi-laboratory evaluation of a common in vitro pepsin digestion assay protocol used in assessing the safety of novel proteins. Regul. Toxicol. Pharmacol. 39, 87-98]; an estimate of exposure of the novel protein(s) to the gastrointestinal tract where absorption occurs (e.g., protein abundance in the crop, processing effects); and when appropriate, specific IgE binding studies or skin prick testing. Additional approaches may be considered (e.g., animal models; targeted sera screening) as the science evolves; however, such approaches have not been thoroughly evaluated or validated for predicting protein allergenicity.

Benchmark data for identifying multi-functional types of membrane proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-09-01

Identifying membrane proteins and their multi-functional types is an indispensable yet challenging topic in proteomics and bioinformatics. In this article, we provide data that are used for training and testing Mem-ADSVM (Wan et al., 2016. "Mem-ADSVM: a two-layer multi-label predictor for identifying multi-functional types of membrane proteins" [1]), a two-layer multi-label predictor for predicting multi-functional types of membrane proteins.

Identifying Bacterial Immune Evasion Proteins Using Phage Display.

PubMed

Fevre, Cindy; Scheepmaker, Lisette; Haas, Pieter-Jan

2017-01-01

Methods aimed at identification of immune evasion proteins are mainly rely on in silico prediction of sequence, structural homology to known evasion proteins or use a proteomics driven approach. Although proven successful these methods are limited by a low efficiency and or lack of functional identification. Here we describe a high-throughput genomic strategy to functionally identify bacterial immune evasion proteins using phage display technology. Genomic bacterial DNA is randomly fragmented and ligated into a phage display vector that is used to create a phage display library expressing bacterial secreted and membrane bound proteins. This library is used to select displayed bacterial secretome proteins that interact with host immune components.

Comparative quantitative proteomic analysis of disease stratified laser captured microdissected human islets identifies proteins and pathways potentially related to type 1 diabetes.

PubMed

Nyalwidhe, Julius O; Grzesik, Wojciech J; Burch, Tanya C; Semeraro, Michele L; Waseem, Tayab; Gerling, Ivan C; Mirmira, Raghavendra G; Morris, Margaret A; Nadler, Jerry L

2017-01-01

Type 1 diabetes (T1D) is a chronic inflammatory disease that is characterized by autoimmune destruction of insulin-producing pancreatic beta cells. The goal of this study was to identify novel protein signatures that distinguish Islets from patients with T1D, patients who are autoantibody positive without symptoms of diabetes, and from individuals with no evidence of disease. High resolution high mass accuracy label free quantitative mass spectrometry analysis was applied to islets isolated by laser capture microdissection from disease stratified human pancreata from the Network for Pancreatic Organ Donors with Diabetes (nPOD), these included donors without diabetes, donors with T1D-associated autoantibodies in the absence of diabetes, and donors with T1D. Thirty-nine proteins were found to be differentially regulated in autoantibody positive cases compared to the no-disease group, with 25 upregulated and 14 downregulated proteins. For the T1D cases, 63 proteins were differentially expressed, with 24 upregulated and 39 downregulated, compared to the no disease controls. We have identified functional annotated enriched gene families and multiple protein-protein interaction clusters of proteins are involved in biological and molecular processes that may have a role in T1D. The proteins that are upregulated in T1D cases include S100A9, S100A8, REG1B, REG3A and C9 amongst others. These proteins have important biological functions, such as inflammation, metabolic regulation, and autoimmunity, all of which are pathways linked to the pathogenesis of T1D. The identified proteins may be involved in T1D development and pathogenesis. Our findings of novel proteins uniquely upregulated in T1D pancreas provides impetus for further investigations focusing on their expression profiles in beta cells/ islets to evaluate their role in the disease pathogenesis. Some of these molecules may be novel therapeutic targets T1D.

Animal models of protein allergenicity: potential benefits, pitfalls and challenges.

PubMed

Dearman, R J; Kimber, I

2009-04-01

Food allergy is an important health issue. With an increasing interest in novel foods derived from transgenic crop plants, there is a growing need for the development of approaches suitable for the characterization of the allergenic potential of proteins. There are methods available currently (such as homology searches and serological testing) that are very effective at identifying proteins that are likely to cross-react with known allergens. However, animal models may play a role in the identification of truly novel proteins, such as bacterial or fungal proteins, that have not been experienced previously in the diet. We consider here the potential benefits, pitfalls and challenges of the selection of various animal models, including the mouse, the rat, the dog and the neonatal swine. The advantages and disadvantages of various experimental end-points are discussed, including the measurement of specific IgE by ELISA, Western blotting or functional tests such as the passive cutaneous anaphylaxis assay, and the assessment of challenge-induced clinical symptoms in previously sensitized animals. The experimental variables of route of exposure to test proteins and the incorporation of adjuvant to increase the sensitivity of the responses are considered also. It is important to emphasize that currently none of these approaches has been validated for the purposes of hazard identification in the context of a safety assessment. However, the available evidence suggests that the judicious use of an accurate and robust animal model could provide important additional data that would contribute significantly to the assessment of the potential allergenicity of novel proteins.

A Non-parametric Cutout Index for Robust Evaluation of Identified Proteins*

PubMed Central

Serang, Oliver; Paulo, Joao; Steen, Hanno; Steen, Judith A.

2013-01-01

This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems. PMID:23292186

Application of M13 phage display for identifying immunogenic proteins from tick (Ixodes scapularis) saliva.

PubMed

Becker, Martin; Felsberger, André; Frenzel, André; Shattuck, Wendy M C; Dyer, Megan; Kügler, Jonas; Zantow, Jonas; Mather, Thomas N; Hust, Michael

2015-05-30

Ticks act as vectors for a large number of different pathogens, perhaps most notably Borrelia burgdorferi, the causative agent of Lyme disease. The most prominent tick vector in the United States is the blacklegged tick, Ixodes scapularis. Tick bites are of special public health concern since there are no vaccines available against most tick-transmitted pathogens. Based on the observation that certain non-natural host animals such as guinea pigs or humans can develop adaptive immune responses to tick bites, anti-tick vaccination is a potential approach to tackle health risks associated with tick bites. The aim of this study was to use an oligopeptide phage display strategy to identify immunogenic salivary gland proteins from I. scapularis that are recognized by human immune sera. Oligopeptide libraries were generated from salivary gland mRNA of 18 h fed nymphal I. scapularis. Eight immunogenic oligopeptides were selected using human immune sera. Three selected immunogenic oligopeptides were cloned and produced as recombinant proteins. The immunogenic character of an identified metalloprotease (MP1) was validated with human sera. This enzyme has been described previously and was hypothesized as immunogenic which was confirmed in this study. Interestingly, it also has close homologs in other Ixodes species. An immunogenic protein of I. scapularis was identified by oligopeptide phage display. MP1 is a potential candidate for vaccine development.

AllergenOnline: A peer-reviewed, curated allergen database to assess novel food proteins for potential cross-reactivity.

PubMed

Goodman, Richard E; Ebisawa, Motohiro; Ferreira, Fatima; Sampson, Hugh A; van Ree, Ronald; Vieths, Stefan; Baumert, Joseph L; Bohle, Barbara; Lalithambika, Sreedevi; Wise, John; Taylor, Steve L

2016-05-01

Increasingly regulators are demanding evaluation of potential allergenicity of foods prior to marketing. Primary risks are the transfer of allergens or potentially cross-reactive proteins into new foods. AllergenOnline was developed in 2005 as a peer-reviewed bioinformatics platform to evaluate risks of new dietary proteins in genetically modified organisms (GMO) and novel foods. The process used to identify suspected allergens and evaluate the evidence of allergenicity was refined between 2010 and 2015. Candidate proteins are identified from the NCBI database using keyword searches, the WHO/IUIS nomenclature database and peer reviewed publications. Criteria to classify proteins as allergens are described. Characteristics of the protein, the source and human subjects, test methods and results are evaluated by our expert panel and archived. Food, inhalant, salivary, venom, and contact allergens are included. Users access allergen sequences through links to the NCBI database and relevant references are listed online. Version 16 includes 1956 sequences from 778 taxonomic-protein groups that are accepted with evidence of allergic serum IgE-binding and/or biological activity. AllergenOnline provides a useful peer-reviewed tool for identifying the primary potential risks of allergy for GMOs and novel foods based on criteria described by the Codex Alimentarius Commission (2003). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ORF phage display to identify cellular proteins with different functions.

PubMed

Li, Wei

2012-09-01

Open reading frame (ORF) phage display is a new branch of phage display aimed at improving its efficiency to identify cellular proteins with specific binding or functional activities. Despite the success of phage display with antibody libraries and random peptide libraries, phage display with cDNA libraries of cellular proteins identifies a high percentage of non-ORF clones encoding unnatural short peptides with minimal biological implications. This is mainly because of the uncontrollable reading frames of cellular proteins in conventional cDNA libraries. ORF phage display solves this problem by eliminating non-ORF clones to generate ORF cDNA libraries. Here I summarize the procedures of ORF phage display, discuss the factors influencing its efficiency, present examples of its versatile applications, and highlight evidence of its capability of identifying biologically relevant cellular proteins. ORF phage display coupled with different selection strategies is capable of delineating diverse functions of cellular proteins with unique advantages. Copyright © 2012 Elsevier Inc. All rights reserved.

Profiling Synaptic Proteins Identifies Regulators of Insulin Secretion and Lifespan

PubMed Central

Kaplan, Joshua M.

2008-01-01

Cells are organized into distinct compartments to perform specific tasks with spatial precision. In neurons, presynaptic specializations are biochemically complex subcellular structures dedicated to neurotransmitter secretion. Activity-dependent changes in the abundance of presynaptic proteins are thought to endow synapses with different functional states; however, relatively little is known about the rules that govern changes in the composition of presynaptic terminals. We describe a genetic strategy to systematically analyze protein localization at Caenorhabditis elegans presynaptic specializations. Nine presynaptic proteins were GFP-tagged, allowing visualization of multiple presynaptic structures. Changes in the distribution and abundance of these proteins were quantified in 25 mutants that alter different aspects of neurotransmission. Global analysis of these data identified novel relationships between particular presynaptic components and provides a new method to compare gene functions by identifying shared protein localization phenotypes. Using this strategy, we identified several genes that regulate secretion of insulin-like growth factors (IGFs) and influence lifespan in a manner dependent on insulin/IGF signaling. PMID:19043554

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Floppy and Rigid Regions in Proteins

NASA Astrophysics Data System (ADS)

Jacobs, D. J.; Thorpe, M. F.; Kuhn, L. A.

1998-03-01

In proteins it is possible to separate hard covalent forces involving bond lengths and bond angles from other weak forces. We model the microstructure of the protein as a generic bar-joint truss framework, where the hard covalent forces and strong hydrogen bonds are regarded as rigid bar constraints. We study the mechanical stability of proteins using FIRST (Floppy Inclusions and Rigid Substructure Topography) based on a recently developed combinatorial constraint counting algorithm (the 3D Pebble Game), which is a generalization of the 2D pebble game (D. J. Jacobs and M. F. Thorpe, ``Generic Rigidity: The Pebble Game'', Phys. Rev. Lett.) 75, 4051-4054 (1995) for the special class of bond-bending networks (D. J. Jacobs, "Generic Rigidity in Three Dimensional Bond-bending Networks", Preprint Aug (1997)). This approach is useful in identifying rigid motifs and flexible linkages in proteins, and thereby determines the essential degrees of freedom. We will show some preliminary results from the FIRST analysis on the myohemerythrin and lyozyme proteins.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

Assessment of the potential pathogenicity of missense mutations identified in the GTPase-activating protein (GAP)-related domain of the neurofibromatosis type-1 (NF1) gene.

PubMed

Thomas, Laura; Richards, Mark; Mort, Matthew; Dunlop, Elaine; Cooper, David N; Upadhyaya, Meena

2012-12-01

Neurofibromatosis type-1 (NF1) is caused by constitutional mutations of the NF1 tumor-suppressor gene. Although ∼85% of inherited NF1 microlesions constitute truncating mutations, the remaining ∼15% are missense mutations whose pathological relevance is often unclear. The GTPase-activating protein-related domain (GRD) of the NF1-encoded protein, neurofibromin, serves to define its major function as a negative regulator of the Ras-MAPK (mitogen-activated protein kinase) signaling pathway. We have established a functional assay to assess the potential pathogenicity of 15 constitutional nonsynonymous NF1 missense mutations (11 novel and 4 previously reported but not functionally characterized) identified in the NF1-GRD (p.R1204G, p.R1204W, p.R1276Q, p.L1301R, p.I1307V, p.T1324N, p.E1327G, p.Q1336R, p.E1356G, p.R1391G, p.V1398D, p.K1409E, p.P1412R, p.K1436Q, p.S1463F). Individual mutations were introduced into an NF1-GRD expression vector and activated Ras was assayed by an enzyme-linked immunosorbent assay (ELISA). Ten NF1-GRD variants were deemed to be potentially pathogenic by virtue of significantly elevated levels of activated GTP-bound Ras in comparison to wild-type NF1 protein. The remaining five NF1-GRD variants were deemed less likely to be of pathological significance as they exhibited similar levels of activated Ras to the wild-type protein. These conclusions received broad support from both bioinformatic analysis and molecular modeling and serve to improve our understanding of NF1-GRD structure and function. © 2012 Wiley Periodicals, Inc.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Proteomic Analysis of the Soybean Symbiosome Identifies New Symbiotic Proteins*

PubMed Central

Clarke, Victoria C.; Loughlin, Patrick C.; Gavrin, Aleksandr; Chen, Chi; Brear, Ella M.; Day, David A.; Smith, Penelope M.C.

2015-01-01

Legumes form a symbiosis with rhizobia in which the plant provides an energy source to the rhizobia bacteria that it uses to fix atmospheric nitrogen. This nitrogen is provided to the legume plant, allowing it to grow without the addition of nitrogen fertilizer. As part of the symbiosis, the bacteria in the infected cells of a new root organ, the nodule, are surrounded by a plant-derived membrane, the symbiosome membrane, which becomes the interface between the symbionts. Fractions containing the symbiosome membrane (SM) and material from the lumen of the symbiosome (peribacteroid space or PBS) were isolated from soybean root nodules and analyzed using nongel proteomic techniques. Bicarbonate stripping and chloroform-methanol extraction of isolated SM were used to reduce complexity of the samples and enrich for hydrophobic integral membrane proteins. One hundred and ninety-seven proteins were identified as components of the SM, with an additional fifteen proteins identified from peripheral membrane and PBS protein fractions. Proteins involved in a range of cellular processes such as metabolism, protein folding and degradation, membrane trafficking, and solute transport were identified. These included a number of proteins previously localized to the SM, such as aquaglyceroporin nodulin 26, sulfate transporters, remorin, and Rab7 homologs. Among the proteome were a number of putative transporters for compounds such as sulfate, calcium, hydrogen ions, peptide/dicarboxylate, and nitrate, as well as transporters for which the substrate is not easy to predict. Analysis of the promoter activity for six genes encoding putative SM proteins showed nodule specific expression, with five showing expression only in infected cells. Localization of two proteins was confirmed using GFP-fusion experiments. The data have been deposited to the ProteomeXchange with identifier PXD001132. This proteome will provide a rich resource for the study of the legume-rhizobium symbiosis. PMID

Antibodies against the mono-methylated arginine-glycine repeat (MMA-RG) of the Epstein-Barr virus nuclear antigen 2 (EBNA2) identify potential cellular proteins targeted in viral transformation.

PubMed

Ayoubian, Hiresh; Fröhlich, Thomas; Pogodski, Dagmar; Flatley, Andrew; Kremmer, Elisabeth; Schepers, Aloys; Feederle, Regina; Arnold, Georg J; Grässer, Friedrich A

2017-08-01

The Epstein-Barr virus is a human herpes virus with oncogenic potential. The virus-encoded nuclear antigen 2 (EBNA2) is a key mediator of viral tumorigenesis. EBNA2 features an arginine-glycine (RG) repeat at amino acids (aa)339-354 that is essential for the transformation of lymphocytes and contains symmetrically (SDMA) and asymmetrically (ADMA) di-methylated arginine residues. The SDMA-modified EBNA2 binds the survival motor neuron protein (SMN), thus mimicking SMD3, a cellular SDMA-containing protein that interacts with SMN. Accordingly, a monoclonal antibody (mAb) specific for the SDMA-modified RG repeat of EBNA2 also binds to SMD3. With the novel mAb 19D4 we now show that EBNA2 contains mono-methylated arginine (MMA) residues within the RG repeat. Using 19D4, we immune-precipitated and analysed by mass spectrometry cellular proteins in EBV-transformed B-cells that feature MMA motifs that are similar to the one in EBNA2. Among the cellular proteins identified, we confirmed by immunoprecipitation and/or Western blot analyses Aly/REF, Coilin, DDX5, FXR1, HNRNPK, LSM4, MRE11, NRIP, nucleolin, PRPF8, RBM26, SMD1 (SNRDP1) and THRAP3 proteins that are either known to contain MMA residues or feature RG repeat sequences that probably serve as methylation substrates. The identified proteins are involved in splicing, tumorigenesis, transcriptional activation, DNA stability and RNA processing or export. Furthermore, we found that several proteins involved in energy metabolism are associated with MMA-modified proteins. Interestingly, the viral EBNA1 protein that features methylated RG repeat motifs also reacted with the antibodies. Our results indicate that the region between aa 34-52 of EBNA1 contains ADMA or SDMA residues, while the region between aa 328-377 mainly contains MMA residues.

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

Identification of immunogenic proteins and evaluation of four recombinant proteins as potential vaccine antigens from Vibrio anguillarum in flounder (Paralichthys olivaceus).

PubMed

Xing, Jing; Xu, Hongsen; Wang, Yang; Tang, Xiaoqian; Sheng, Xiuzhen; Zhan, Wenbin

2017-05-31

Vibrio anguillarum is a severe bacterial pathogen that can infect a wide range of fish species. Identification of immunogenic proteins and development of vaccine are essential for disease prevention. In this study, immunogenic proteins were screened and identified from V. anguillarum, and then protective efficacy of the immunogenic proteins was evaluated. Immunogenic proteins in V. anguillarum whole cell were detected by Western blotting (WB) using immunized flounder (Paralichthys olivaceus) serum, and then identified by Mass spectrometry (MS). The recombinant proteins of four identified immunogenic proteins were produced and immunized to fish, and then percentages of surface membrane immunoglobulin-positive (sIg+) cells in peripheral blood lymphocytes (PBL), total antibodies, antibodies against V. anguillarum, antibodies against recombinant proteins and relative percent survival (RPS) were measured, respectively. The results showed that five immunogenic proteins, VAA, Groel, OmpU, PteF and SpK, were identified; their recombinant proteins, rOmpU, rGroel, rSpK and rVAA, could induce the proliferation of sIg+ cells in PBL and production of total antibodies, antibodies against V. anguillarum and antibodies against the recombinant proteins; their protection against V. anguillarum showed 64.86%, 72.97%, 21.62% and 78.38% RPS, respectively. The results revealed that the immunoproteomic technique using fish anti-V. anguillarum serum provided an efficient way to screen the immunogenic protein for vaccine antigen. Moreover, the rVAA, rGroel and rOmpU had potential to be vaccine candidates against V. anguillarum infection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploiting genomic data to identify proteins involved in abalone reproduction.

PubMed

Mendoza-Porras, Omar; Botwright, Natasha A; McWilliam, Sean M; Cook, Mathew T; Harris, James O; Wijffels, Gene; Colgrave, Michelle L

2014-08-28

Aside from their critical role in reproduction, abalone gonads serve as an indicator of sexual maturity and energy balance, two key considerations for effective abalone culture. Temperate abalone farmers face issues with tank restocking with highly marketable abalone owing to inefficient spawning induction methods. The identification of key proteins in sexually mature abalone will serve as the foundation for a greater understanding of reproductive biology. Addressing this knowledge gap is the first step towards improving abalone aquaculture methods. Proteomic profiling of female and male gonads of greenlip abalone, Haliotis laevigata, was undertaken using liquid chromatography-mass spectrometry. Owing to the incomplete nature of abalone protein databases, in addition to searching against two publicly available databases, a custom database comprising genomic data was used. Overall, 162 and 110 proteins were identified in females and males respectively with 40 proteins common to both sexes. For proteins involved in sexual maturation, sperm and egg structure, motility, acrosomal reaction and fertilization, 23 were identified only in females, 18 only in males and 6 were common. Gene ontology analysis revealed clear differences between the female and male protein profiles reflecting a higher rate of protein synthesis in the ovary and higher metabolic activity in the testis. A comprehensive mass spectrometry-based analysis was performed to profile the abalone gonad proteome providing the foundation for future studies of reproduction in abalone. Key proteins involved in both reproduction and energy balance were identified. Genomic resources were utilised to build a database of molluscan proteins yielding >60% more protein identifications than in a standard workflow employing public protein databases. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of membrane-associated proteins with pathogenic potential expressed by Corynebacterium pseudotuberculosis grown in animal serum.

PubMed

Raynal, José Tadeu; Bastos, Bruno Lopes; Vilas-Boas, Priscilla Carolinne Bagano; Sousa, Thiago de Jesus; Costa-Silva, Marcos; de Sá, Maria da Conceição Aquino; Portela, Ricardo Wagner; Moura-Costa, Lília Ferreira; Azevedo, Vasco; Meyer, Roberto

2018-01-25

Previous works defining antigens that might be used as vaccine targets against Corynebacterium pseudotuberculosis, which is the causative agent of sheep and goat caseous lymphadenitis, have focused on secreted proteins produced in a chemically defined culture media. Considering that such antigens might not reflect the repertoire of proteins expressed during infection conditions, this experiment aimed to investigate the membrane-associated proteins with pathogenic potential expressed by C. pseudotuberculosis grown directly in animal serum. Its membrane-associated proteins have been extracted using an organic solvent enrichment methodology, followed by LC-MS/MS and bioinformatics analysis for protein identification and classification. The results revealed 22 membrane-associated proteins characterized as potentially pathogenic. An interaction network analysis indicated that the four potentially pathogenic proteins ciuA, fagA, OppA4 and OppCD were biologically connected within two distinct network pathways, which were both associated with the ABC Transporters KEGG pathway. These results suggest that C. pseudotuberculosis pathogenesis might be associated with the transport and uptake of nutrients; other seven identified potentially pathogenic membrane proteins also suggest that pathogenesis might involve events of bacterial resistance and adhesion. The proteins herein reported potentially reflect part of the protein repertoire expressed during real infection conditions and might be tested as vaccine antigens.

Mapping the membrane proteome of anaerobic gut fungi identifies a wealth of carbohydrate binding proteins and transporters.

PubMed

Seppälä, Susanna; Solomon, Kevin V; Gilmore, Sean P; Henske, John K; O'Malley, Michelle A

2016-12-20

Engineered cell factories that convert biomass into value-added compounds are emerging as a timely alternative to petroleum-based industries. Although often overlooked, integral membrane proteins such as solute transporters are pivotal for engineering efficient microbial chassis. Anaerobic gut fungi, adapted to degrade raw plant biomass in the intestines of herbivores, are a potential source of valuable transporters for biotechnology, yet very little is known about the membrane constituents of these non-conventional organisms. Here, we mined the transcriptome of three recently isolated strains of anaerobic fungi to identify membrane proteins responsible for sensing and transporting biomass hydrolysates within a competitive and rather extreme environment. Using sequence analyses and homology, we identified membrane protein-coding sequences from assembled transcriptomes from three strains of anaerobic gut fungi: Neocallimastix californiae, Anaeromyces robustus, and Piromyces finnis. We identified nearly 2000 transporter components: about half of these are involved in the general secretory pathway and intracellular sorting of proteins; the rest are predicted to be small-solute transporters. Unexpectedly, we found a number of putative sugar binding proteins that are associated with prokaryotic uptake systems; and approximately 100 class C G-protein coupled receptors (GPCRs) with non-canonical putative sugar binding domains. We report the first comprehensive characterization of the membrane protein machinery of biotechnologically relevant anaerobic gut fungi. Apart from identifying conserved machinery for protein sorting and secretion, we identify a large number of putative solute transporters that are of interest for biotechnological applications. Notably, our data suggests that the fungi display a plethora of carbohydrate binding domains at their surface, perhaps as a means to sense and sequester some of the sugars that their biomass degrading, extracellular enzymes

Carbonylated plasma proteins as potential biomarkers of obesity induced type 2 diabetes mellitus.

PubMed

Bollineni, Ravi Chand; Fedorova, Maria; Blüher, Matthias; Hoffmann, Ralf

2014-11-07

Protein carbonylation is a common nonenzymatic oxidative post-translational modification, which is often considered as biomarker of oxidative stress. Recent evidence links protein carbonylation also to obesity and type 2 diabetes mellitus (T2DM), though the protein targets of carbonylation in human plasma have not been identified. In this study, we profiled carbonylated proteins in plasma samples obtained from lean individuals and obese patients with or without T2DM. The plasma samples were digested with trypsin, carbonyl groups were derivatized with O-(biotinylcarbazoylmethyl)hydroxylamine, enriched by avidin affinity chromatography, and analyzed by RPC-MS/MS. Signals of potentially modified peptides were targeted in a second LC-MS/MS analysis to retrieve the peptide sequence and the modified residues. A total of 158 unique carbonylated proteins were identified, of which 52 were detected in plasma samples of all three groups. Interestingly, 36 carbonylated proteins were detected only in obese patients with T2DM, whereas 18 were detected in both nondiabetic groups. The carbonylated proteins originated mostly from liver, plasma, platelet, and endothelium. Functionally, they were mainly involved in cell adhesion, signaling, angiogenesis, and cytoskeletal remodeling. Among the identified carbonylated proteins were several candidates, such as VEGFR-2, MMP-1, argin, MKK4, and compliment C5, already connected before to diabetes, obesity and metabolic diseases.

A newly identified protein of Leptospira interrogans mediates binding to laminin.

PubMed

Longhi, Mariana T; Oliveira, Tatiane R; Romero, Eliete C; Gonçales, Amane P; de Morais, Zenaide M; Vasconcellos, Silvio A; Nascimento, Ana L T O

2009-10-01

Pathogenic Leptospira is the aetiological agent of leptospirosis, a life-threatening disease that affects populations worldwide. The search for novel antigens that could be relevant in host-pathogen interactions is being pursued. These antigens have the potential to elicit several activities, including adhesion. This study focused on a hypothetical predicted lipoprotein of Leptospira, encoded by the gene LIC12895, thought to mediate attachment to extracellular matrix (ECM) components. The gene was cloned and expressed in Escherichia coli BL21 Star (DE3)pLys by using the expression vector pAE. The recombinant protein tagged with N-terminal hexahistidine was purified by metal-charged chromatography and characterized by circular dichroism spectroscopy. The capacity of the protein to mediate attachment to ECM components was evaluated by binding assays. The leptospiral protein encoded by LIC12895, named Lsa27 (leptospiral surface adhesin, 27 kDa), bound strongly to laminin in a dose-dependent and saturable fashion. Moreover, Lsa27 was recognized by antibodies from serum samples of confirmed leptospirosis specimens in both the initial and the convalescent phases of the disease. Lsa27 is most likely a surface protein of Leptospira as revealed in liquid-phase immunofluorescence assays with living organisms. Taken together, these data indicate that this newly identified membrane protein is expressed during natural infection and may play a role in mediating adhesion of L. interrogans to its host.

Potential of plant proteins for medical applications.

PubMed

Reddy, Narendra; Yang, Yiqi

2011-10-01

Various natural and synthetic polymers are being explored to develop biomaterials for tissue engineering and drug delivery. Although proteins are preferable over carbohydrates and synthetic polymers, biomaterials developed from proteins lack the mechanical properties and/or biocompatibilities required for medical applications. Plant proteins are widely available, have low potential to be immunogenic and can be made into fibers, films, hydrogels and micro- and nano-particles for medical applications. Studies, mostly with zein, have demonstrated the potential of using plant proteins for tissue engineering and drug delivery. Although other plant proteins such as wheat gluten and soyproteins have also shown biocompatibility using in vitro studies, fabricating biomaterials such as nano-fibers and nano-particles from soy and wheat proteins offers considerable challenges. Copyright © 2011. Published by Elsevier Ltd.

Theranostic potential of gold nanoparticle-protein agglomerates

NASA Astrophysics Data System (ADS)

Sanpui, Pallab; Paul, Anumita; Chattopadhyay, Arun

2015-11-01

Owing to the ever-increasing applications, glittered with astonishing success of gold nanoparticles (Au NPs) in biomedical research as diagnostic and therapeutic agents, the study of Au NP-protein interaction seems critical for maximizing their theranostic efficiency, and thus demands comprehensive understanding. The mutual interaction of Au NPs and proteins at physiological conditions may result in the aggregation of protein, which can ultimately lead to the formation of Au NP-protein agglomerates. In the present article, we try to appreciate the plausible steps involved in the Au NP-induced aggregation of proteins and also the importance of the proteins' three-dimensional structures in the process. The Au NP-protein agglomerates can potentially be exploited for efficient loading and subsequent release of various therapeutically important molecules, including anticancer drugs, with the unique opportunity of incorporating hydrophilic as well as hydrophobic drugs in the same nanocarrier system. Moreover, the Au NP-protein agglomerates can act as `self-diagnostic' systems, allowing investigation of the conformational state of the associated protein(s) as well as the protein-protein or protein-Au NP interaction within the agglomerates. Furthermore, the potential of these Au NP-protein agglomerates as a novel platform for multifunctional theranostic application along with exciting future-possibilities is highlighted here.

Effective Potentials for Folding Proteins

NASA Astrophysics Data System (ADS)

Chen, Nan-Yow; Su, Zheng-Yao; Mou, Chung-Yu

2006-02-01

A coarse-grained off-lattice model that is not biased in any way to the native state is proposed to fold proteins. To predict the native structure in a reasonable time, the model has included the essential effects of water in an effective potential. Two new ingredients, the dipole-dipole interaction and the local hydrophobic interaction, are introduced and are shown to be as crucial as the hydrogen bonding. The model allows successful folding of the wild-type sequence of protein G and may have provided important hints to the study of protein folding.

All-Atom Four-Body Knowledge-Based Statistical Potentials to Distinguish Native Protein Structures from Nonnative Folds

PubMed Central

2017-01-01

Recent advances in understanding protein folding have benefitted from coarse-grained representations of protein structures. Empirical energy functions derived from these techniques occasionally succeed in distinguishing native structures from their corresponding ensembles of nonnative folds or decoys which display varying degrees of structural dissimilarity to the native proteins. Here we utilized atomic coordinates of single protein chains, comprising a large diverse training set, to develop and evaluate twelve all-atom four-body statistical potentials obtained by exploring alternative values for a pair of inherent parameters. Delaunay tessellation was performed on the atomic coordinates of each protein to objectively identify all quadruplets of interacting atoms, and atomic potentials were generated via statistical analysis of the data and implementation of the inverted Boltzmann principle. Our potentials were evaluated using benchmarking datasets from Decoys-‘R'-Us, and comparisons were made with twelve other physics- and knowledge-based potentials. Ranking 3rd, our best potential tied CHARMM19 and surpassed AMBER force field potentials. We illustrate how a generalized version of our potential can be used to empirically calculate binding energies for target-ligand complexes, using HIV-1 protease-inhibitor complexes for a practical application. The combined results suggest an accurate and efficient atomic four-body statistical potential for protein structure prediction and assessment. PMID:29119109

Unbiased screen identifies aripiprazole as a modulator of abundance of the polyglutamine disease protein, ataxin-3

PubMed Central

Costa, Maria do Carmo; Ashraf, Naila S.; Fischer, Svetlana; Yang, Yemen; Schapka, Emily; Joshi, Gnanada; McQuade, Thomas J.; Dharia, Rahil M.; Dulchavsky, Mark; Ouyang, Michelle; Cook, David; Sun, Duxin; Larsen, Martha J.; Gestwicki, Jason E.; Todi, Sokol V.; Ivanova, Magdalena I.; Paulson, Henry L.

2016-01-01

No disease-modifying treatment exists for the fatal neurodegenerative polyglutamine disease known both as Machado-Joseph disease and spinocerebellar ataxia type 3. As a potential route to therapy, we identified small molecules that reduce levels of the mutant disease protein, ATXN3. Screens of a small molecule collection, including 1250 Food and Drug Administration-approved drugs, in a novel cell-based assay, followed by secondary screens in brain slice cultures from transgenic mice expressing the human disease gene, identified the atypical antipsychotic aripiprazole as one of the hits. Aripiprazole increased longevity in a Drosophila model of Machado-Joseph disease and effectively reduced aggregated ATXN3 species in flies and in brains of transgenic mice treated for 10 days. The aripiprazole-mediated decrease in ATXN3 abundance may reflect a complex response culminating in the modulation of specific components of cellular protein homeostasis. Aripiprazole represents a potentially promising therapeutic drug for Machado-Joseph disease and possibly other neurological proteinopathies. PMID:27645800

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome.

PubMed

Higuera, Clara; Gardiner, Katheleen J; Cios, Krzysztof J

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

PubMed Central

Higuera, Clara; Gardiner, Katheleen J.; Cios, Krzysztof J.

2015-01-01

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets. PMID:26111164

Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

PubMed

Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

2018-01-01

We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation.  Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases.  We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes.  Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.

Mapping the membrane proteome of anaerobic gut fungi identifies a wealth of carbohydrate binding proteins and transporters

DOE PAGES

Seppala, Susanna; Solomon, Kevin V.; Gilmore, Sean P.; ...

2016-12-20

Here, engineered cell factories that convert biomass into value-added compounds are emerging as a timely alternative to petroleum-based industries. Although often overlooked, integral membrane proteins such as solute transporters are pivotal for engineering efficient microbial chassis. Anaerobic gut fungi, adapted to degrade raw plant biomass in the intestines of herbivores, are a potential source of valuable transporters for biotechnology, yet very little is known about the membrane constituents of these non-conventional organisms. Here, we mined the transcriptome of three recently isolated strains of anaerobic fungi to identify membrane proteins responsible for sensing and transporting biomass hydrolysates within a competitive andmore » rather extreme environment. Using sequence analyses and homology, we identified membrane protein-coding sequences from assembled transcriptomes from three strains of anaerobic gut fungi: Neocallimastix californiae, Anaeromyces robustus, and Piromyces finnis. We identified nearly 2000 transporter components: about half of these are involved in the general secretory pathway and intracellular sorting of proteins; the rest are predicted to be small-solute transporters. Unexpectedly, we found a number of putative sugar binding proteins that are associated with prokaryotic uptake systems; and approximately 100 class C G-protein coupled receptors (GPCRs) with non-canonical putative sugar binding domains. In conclusion, we report the first comprehensive characterization of the membrane protein machinery of biotechnologically relevant anaerobic gut fungi. Apart from identifying conserved machinery for protein sorting and secretion, we identify a large number of putative solute transporters that are of interest for biotechnological applications. Notably, our data suggests that the fungi display a plethora of carbohydrate binding domains at their surface, perhaps as a means to sense and sequester some of the sugars that their biomass

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2018-04-30

Spontaneous preterm birth (sPTB) remains a major clinical dilemma; current diagnostics and interventions have not reduced the rate of this serious healthcare burden. This study characterizes differential protein profiles and post-translational modifications (PTMs) in first trimester maternal serum using a refined top-down approach coupling two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) to directly compare subsequent term and preterm labour events and identify marked protein differences. 30 proteoforms were found to be significantly increased or decreased in the sPTB group including 9 phosphoproteins and 11 glycoproteins. Changes occurred in proteins associated with immune and defence responses. We identified protein species that are associated with several clinically relevant biological processes, including interrelated biological networks linked to regulation of the complement cascade and coagulation pathways, immune modulation, metabolic processes and cell signalling. The finding of altered proteoforms in maternal serum from pregnancies that delivered preterm suggests these as potential early biomarkers of sPTB and also possible mediators of the disorder. Identifying changes in protein profiles is critical in the study of cell biology, and disease treatment and prevention. Identifying consistent changes in the maternal serum proteome during early pregnancy, including specific protein PTMs (e.g. phosphorylation, glycosylation), is likely to provide better opportunities for prediction, intervention and prevention of preterm birth. This is the first study to examine first trimester maternal serum using a highly refined top-down proteomic analytical approach based on high resolution 2DE coupled with mass spectrometry to directly compare preterm (<37 weeks) and preterm (≥37 weeks) events and identify select protein differences between these conditions. As such, the data present a promising avenue for translation of biomarker discovery to a

New proteins identified in epididymal fluid from the platypus (Ornithorhynchus anatinus).

PubMed

Dacheux, Jean-Louis; Dacheux, Francoise; Labas, Valerie; Ecroyd, Heath; Nixon, Brett; Jones, Russell C

2009-01-01

The platypus epididymal proteome is being studied because epididymal proteins are essential for male fertility in mammals and it is considered that knowledge of the epididymal proteome in an early mammal would be informative in assessing the convergence and divergence of proteins that are important in the function of the mammalian epididymis. Few of the epididymal proteins that have been identified in eutherian mammals were found in platypus caudal epididymal fluid, and the major epididymal proteins in the platypus (PXN-FBPL, SPARC and E-OR20) have never been identified in the epididymis of any other mammal.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

NASA Astrophysics Data System (ADS)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts

PubMed Central

Frenkel-Morgenstern, Milana; Lacroix, Vincent; Ezkurdia, Iakes; Levin, Yishai; Gabashvili, Alexandra; Prilusky, Jaime; del Pozo, Angela; Tress, Michael; Johnson, Rory; Guigo, Roderic; Valencia, Alfonso

2012-01-01

Chimeric RNAs comprise exons from two or more different genes and have the potential to encode novel proteins that alter cellular phenotypes. To date, numerous putative chimeric transcripts have been identified among the ESTs isolated from several organisms and using high throughput RNA sequencing. The few corresponding protein products that have been characterized mostly result from chromosomal translocations and are associated with cancer. Here, we systematically establish that some of the putative chimeric transcripts are genuinely expressed in human cells. Using high throughput RNA sequencing, mass spectrometry experimental data, and functional annotation, we studied 7424 putative human chimeric RNAs. We confirmed the expression of 175 chimeric RNAs in 16 human tissues, with an abundance varying from 0.06 to 17 RPKM (Reads Per Kilobase per Million mapped reads). We show that these chimeric RNAs are significantly more tissue-specific than non-chimeric transcripts. Moreover, we present evidence that chimeras tend to incorporate highly expressed genes. Despite the low expression level of most chimeric RNAs, we show that 12 novel chimeras are translated into proteins detectable in multiple shotgun mass spectrometry experiments. Furthermore, we confirm the expression of three novel chimeric proteins using targeted mass spectrometry. Finally, based on our functional annotation of exon organization and preserved domains, we discuss the potential features of chimeric proteins with illustrative examples and suggest that chimeras significantly exploit signal peptides and transmembrane domains, which can alter the cellular localization of cognate proteins. Taken together, these findings establish that some chimeric RNAs are translated into potentially functional proteins in humans. PMID:22588898

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1.

PubMed

Ding, Dewu; Sun, Xiao

2018-01-16

Shewanella oneidensis MR-1 can transfer electrons from the intracellular environment to the extracellular space of the cells to reduce the extracellular insoluble electron acceptors (Extracellular Electron Transfer, EET). Benefiting from this EET capability, Shewanella has been widely used in different areas, such as energy production, wastewater treatment, and bioremediation. Genome-wide proteomics data was used to determine the active proteins involved in activating the EET process. We identified 1012 proteins with decreased expression and 811 proteins with increased expression when the EET process changed from inactivation to activation. We then networked these proteins to construct the active protein networks, and identified the top 20 key active proteins by network centralization analysis, including metabolism- and energy-related proteins, signal and transcriptional regulatory proteins, translation-related proteins, and the EET-related proteins. We also constructed the integrated protein interaction and transcriptional regulatory networks for the active proteins, then found three exclusive active network motifs involved in activating the EET process-Bi-feedforward Loop, Regulatory Cascade with a Feedback, and Feedback with a Protein-Protein Interaction (PPI)-and identified the active proteins involved in these motifs. Both enrichment analysis and comparative analysis to the whole-genome data implicated the multiheme c -type cytochromes and multiple signal processing proteins involved in the process. Furthermore, the interactions of these motif-guided active proteins and the involved functional modules were discussed. Collectively, by using network-based methods, this work reported a proteome-wide search for the key active proteins that potentially activate the EET process.

Temporal Profiling and Pulsed SILAC Labeling Identify Novel Secreted Proteins During Ex Vivo Osteoblast Differentiation of Human Stromal Stem Cells*

PubMed Central

Kristensen, Lars P.; Chen, Li; Nielsen, Maria Overbeck; Qanie, Diyako W.; Kratchmarova, Irina; Kassem, Moustapha; Andersen, Jens S.

2012-01-01

It is well established that bone forming cells (osteoblasts) secrete proteins with autocrine, paracrine, and endocrine function. However, the identity and functional role for the majority of these secreted and differentially expressed proteins during the osteoblast (OB) differentiation process, is not fully established. To address these questions, we quantified the temporal dynamics of the human stromal (mesenchymal, skeletal) stem cell (hMSC) secretome during ex vivo OB differentiation using stable isotope labeling by amino acids in cell culture (SILAC). In addition, we employed pulsed SILAC labeling to distinguish genuine secreted proteins from intracellular contaminants. We identified 466 potentially secreted proteins that were quantified at 5 time-points during 14-days ex vivo OB differentiation including 41 proteins known to be involved in OB functions. Among these, 315 proteins exhibited more than 2-fold up or down-regulation. The pulsed SILAC method revealed a strong correlation between the fraction of isotope labeling and the subset of proteins known to be secreted and involved in OB differentiation. We verified SILAC data using qRT-PCR analysis of 9 identified potential novel regulators of OB differentiation. Furthermore, we studied the biological effects of one of these proteins, the hormone stanniocalcin 2 (STC2) and demonstrated its autocrine effects in enhancing osteoblastic differentiation of hMSC. In conclusion, combining complete and pulsed SILAC labeling facilitated the identification of novel factors produced by hMSC with potential role in OB differentiation. Our study demonstrates that the secretome of osteoblastic cells is more complex than previously reported and supports the emerging evidence that osteoblastic cells secrete proteins with endocrine functions and regulate cellular processes beyond bone formation. PMID:22801418

Proteins QSAR with Markov average electrostatic potentials.

PubMed

González-Díaz, Humberto; Uriarte, Eugenio

2005-11-15

Classic physicochemical and topological indices have been largely used in small molecules QSAR but less in proteins QSAR. In this study, a Markov model is used to calculate, for the first time, average electrostatic potentials xik for an indirect interaction between aminoacids placed at topologic distances k within a given protein backbone. The short-term average stochastic potential xi1 for 53 Arc repressor mutants was used to model the effect of Alanine scanning on thermal stability. The Arc repressor is a model protein of relevance for biochemical studies on bioorganics and medicinal chemistry. A linear discriminant analysis model developed correctly classified 43 out of 53, 81.1% of proteins according to their thermal stability. More specifically, the model classified 20/28, 71.4% of proteins with near wild-type stability and 23/25, 92.0% of proteins with reduced stability. Moreover, predictability in cross-validation procedures was of 81.0%. Expansion of the electrostatic potential in the series xi0, xi1, xi2, and xi3, justified the use of the abrupt truncation approach, being the overall accuracy >70.0% for xi0 but equal for xi1, xi2, and xi3. The xi1 model compared favorably with respect to others based on D-Fire potential, surface area, volume, partition coefficient, and molar refractivity, with less than 77.0% of accuracy [Ramos de Armas, R.; González-Díaz, H.; Molina, R.; Uriarte, E. Protein Struct. Func. Bioinf.2004, 56, 715]. The xi1 model also has more tractable interpretation than others based on Markovian negentropies and stochastic moments. Finally, the model is notably simpler than the two models based on quadratic and linear indices. Both models, reported by Marrero-Ponce et al., use four-to-five time more descriptors. Introduction of average stochastic potentials may be useful for QSAR applications; having xik amenable physical interpretation and being very effective.

Expression, Localization of SUMO-1, and Analyses of Potential SUMOylated Proteins in Bubalus bubalis Spermatozoa

PubMed Central

Brohi, Rahim Dad; Wang, Li; Hassine, Najla Ben; Cao, Jing; Talpur, Hira Sajjad; Wu, Di; Huang, Chun-Jie; Rehman, Zia-Ur; Bhattarai, Dinesh; Huo, Li-Jun

2017-01-01

Mature spermatozoa have highly condensed DNA that is essentially silent both transcriptionally and translationally. Therefore, post translational modifications are very important for regulating sperm motility, morphology, and for male fertility in general. Protein sumoylation was recently demonstrated in human and rodent spermatozoa, with potential consequences for sperm motility and DNA integrity. We examined the expression and localization of small ubiquitin-related modifier-1 (SUMO-1) in the sperm of water buffalo (Bubalus bubalis) using immunofluorescence analysis. We confirmed the expression of SUMO-1 in the acrosome. We further found that SUMO-1 was lost if the acrosome reaction was induced by calcium ionophore A23187. Proteins modified or conjugated by SUMO-1 in water buffalo sperm were pulled down and analyzed by mass spectrometry. Sixty proteins were identified, including proteins important for sperm morphology and motility, such as relaxin receptors and cytoskeletal proteins, including tubulin chains, actins, and dyneins. Forty-six proteins were predicted as potential sumoylation targets. The expression of SUMO-1 in the acrosome region of water buffalo sperm and the identification of potentially SUMOylated proteins important for sperm function implicates sumoylation as a crucial PTM related to sperm function. PMID:28659810

Immunoreactive Coxiella burnetii Nine Mile proteins separated by 2D electrophoresis and identified by tandem mass spectrometry

PubMed Central

Deringer, James R.; Chen, Chen; Samuel, James E.; Brown, Wendy C.

2011-01-01

Coxiella burnetii is a Gram-negative obligate intracellular pathogen and the causative agent of Q fever in humans. Q fever causes acute flu-like symptoms and may develop into a chronic disease leading to endocarditis. Its potential as a bioweapon has led to its classification as a category B select agent. An effective inactivated whole-cell vaccine (WCV) currently exists but causes severe granulomatous/necrotizing reactions in individuals with prior exposure, and is not licensed for use in most countries. Current efforts to reduce or eliminate the deleterious reactions associated with WCVs have focused on identifying potential subunit vaccine candidates. Both humoral and T cell-mediated responses are required for protection in animal models. In this study, nine novel immunogenic C. burnetii proteins were identified in extracted whole-cell lysates using 2D electrophoresis, immunoblotting with immune guinea pig sera, and tandem MS. The immunogenic C. burnetii proteins elicited antigen-specific IgG in guinea pigs vaccinated with whole-cell killed Nine Mile phase I vaccine, suggesting a T cell-dependent response. Eleven additional proteins previously shown to react with immune human sera were also antigenic in guinea pigs, showing the relevance of the guinea pig immunization model for antigen discovery. The antigens described here warrant further investigation to validate their potential use as subunit vaccine candidates. PMID:21030434

Capturing the Interaction Potential of Amyloidogenic Proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Javid, Nadeem; Vogtt, Karsten; Winter, Roland

2007-07-13

Experimentally derived static structure factors obtained for the aggregation-prone protein insulin were analyzed with a statistical mechanical model based on the Derjaguin-Landau-Verwey-Overbeek potential. The data reveal that the protein self-assembles into equilibrium clusters already at low concentrations. Furthermore, striking differences regarding interaction forces between aggregation-prone proteins such as insulin in the preaggregated regime and natively stable globular proteins are found.

Identifying protein domains by global analysis of soluble fragment data.

PubMed

Bulloch, Esther M M; Kingston, Richard L

2014-11-15

The production and analysis of individual structural domains is a common strategy for studying large or complex proteins, which may be experimentally intractable in their full-length form. However, identifying domain boundaries is challenging if there is little structural information concerning the protein target. One experimental procedure for mapping domains is to screen a library of random protein fragments for solubility, since truncation of a domain will typically expose hydrophobic groups, leading to poor fragment solubility. We have coupled fragment solubility screening with global data analysis to develop an effective method for identifying structural domains within a protein. A gene fragment library is generated using mechanical shearing, or by uracil doping of the gene and a uracil-specific enzymatic digest. A split green fluorescent protein (GFP) assay is used to screen the corresponding protein fragments for solubility when expressed in Escherichia coli. The soluble fragment data are then analyzed using two complementary approaches. Fragmentation "hotspots" indicate possible interdomain regions. Clustering algorithms are used to group related fragments, and concomitantly predict domain location. The effectiveness of this Domain Seeking procedure is demonstrated by application to the well-characterized human protein p85α. Copyright © 2014 Elsevier Inc. All rights reserved.

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites

NASA Astrophysics Data System (ADS)

Lu, Cheng-Tsung; Chen, Shu-An; Bretaña, Neil Arvin; Cheng, Tzu-Hsiu; Lee, Tzong-Yi

2011-10-01

In proteins, glutamate (Glu) residues are transformed into γ-carboxyglutamate (Gla) residues in a process called carboxylation. The process of protein carboxylation catalyzed by γ-glutamyl carboxylase is deemed to be important due to its involvement in biological processes such as blood clotting cascade and bone growth. There is an increasing interest within the scientific community to identify protein carboxylation sites. However, experimental identification of carboxylation sites via mass spectrometry-based methods is observed to be expensive, time-consuming, and labor-intensive. Thus, we were motivated to design a computational method for identifying protein carboxylation sites. This work aims to investigate the protein carboxylation by considering the composition of amino acids that surround modification sites. With the implication of a modified residue prefers to be accessible on the surface of a protein, the solvent-accessible surface area (ASA) around carboxylation sites is also investigated. Radial basis function network is then employed to build a predictive model using various features for identifying carboxylation sites. Based on a five-fold cross-validation evaluation, a predictive model trained using the combined features of amino acid sequence (AA20D), amino acid composition, and ASA, yields the highest accuracy at 0.874. Furthermore, an independent test done involving data not included in the cross-validation process indicates that in silico identification is a feasible means of preliminary analysis. Additionally, the predictive method presented in this work is implemented as Carboxylator (http://csb.cse.yzu.edu.tw/Carboxylator/), a web-based tool for identifying carboxylated proteins with modification sites in order to help users in investigating γ-glutamyl carboxylation.

A Novel Highly Divergent Protein Family Identified from a Viviparous Insect by RNA-seq Analysis: A Potential Target for Tsetse Fly-Specific Abortifacients

PubMed Central

Benoit, Joshua B.; Attardo, Geoffrey M.; Michalkova, Veronika; Krause, Tyler B.; Bohova, Jana; Zhang, Qirui; Baumann, Aaron A.; Mireji, Paul O.; Takáč, Peter; Denlinger, David L.; Ribeiro, Jose M.; Aksoy, Serap

2014-01-01

In tsetse flies, nutrients for intrauterine larval development are synthesized by the modified accessory gland (milk gland) and provided in mother's milk during lactation. Interference with at least two milk proteins has been shown to extend larval development and reduce fecundity. The goal of this study was to perform a comprehensive characterization of tsetse milk proteins using lactation-specific transcriptome/milk proteome analyses and to define functional role(s) for the milk proteins during lactation. Differential analysis of RNA-seq data from lactating and dry (non-lactating) females revealed enrichment of transcripts coding for protein synthesis machinery, lipid metabolism and secretory proteins during lactation. Among the genes induced during lactation were those encoding the previously identified milk proteins (milk gland proteins 1–3, transferrin and acid sphingomyelinase 1) and seven new genes (mgp4–10). The genes encoding mgp2–10 are organized on a 40 kb syntenic block in the tsetse genome, have similar exon-intron arrangements, and share regions of amino acid sequence similarity. Expression of mgp2–10 is female-specific and high during milk secretion. While knockdown of a single mgp failed to reduce fecundity, simultaneous knockdown of multiple variants reduced milk protein levels and lowered fecundity. The genomic localization, gene structure similarities, and functional redundancy of MGP2–10 suggest that they constitute a novel highly divergent protein family. Our data indicates that MGP2–10 function both as the primary amino acid resource for the developing larva and in the maintenance of milk homeostasis, similar to the function of the mammalian casein family of milk proteins. This study underscores the dynamic nature of the lactation cycle and identifies a novel family of lactation-specific proteins, unique to Glossina sp., that are essential to larval development. The specificity of MGP2–10 to tsetse and their critical role during

A novel highly divergent protein family identified from a viviparous insect by RNA-seq analysis: a potential target for tsetse fly-specific abortifacients.

PubMed

Benoit, Joshua B; Attardo, Geoffrey M; Michalkova, Veronika; Krause, Tyler B; Bohova, Jana; Zhang, Qirui; Baumann, Aaron A; Mireji, Paul O; Takáč, Peter; Denlinger, David L; Ribeiro, Jose M; Aksoy, Serap

2014-04-01

In tsetse flies, nutrients for intrauterine larval development are synthesized by the modified accessory gland (milk gland) and provided in mother's milk during lactation. Interference with at least two milk proteins has been shown to extend larval development and reduce fecundity. The goal of this study was to perform a comprehensive characterization of tsetse milk proteins using lactation-specific transcriptome/milk proteome analyses and to define functional role(s) for the milk proteins during lactation. Differential analysis of RNA-seq data from lactating and dry (non-lactating) females revealed enrichment of transcripts coding for protein synthesis machinery, lipid metabolism and secretory proteins during lactation. Among the genes induced during lactation were those encoding the previously identified milk proteins (milk gland proteins 1-3, transferrin and acid sphingomyelinase 1) and seven new genes (mgp4-10). The genes encoding mgp2-10 are organized on a 40 kb syntenic block in the tsetse genome, have similar exon-intron arrangements, and share regions of amino acid sequence similarity. Expression of mgp2-10 is female-specific and high during milk secretion. While knockdown of a single mgp failed to reduce fecundity, simultaneous knockdown of multiple variants reduced milk protein levels and lowered fecundity. The genomic localization, gene structure similarities, and functional redundancy of MGP2-10 suggest that they constitute a novel highly divergent protein family. Our data indicates that MGP2-10 function both as the primary amino acid resource for the developing larva and in the maintenance of milk homeostasis, similar to the function of the mammalian casein family of milk proteins. This study underscores the dynamic nature of the lactation cycle and identifies a novel family of lactation-specific proteins, unique to Glossina sp., that are essential to larval development. The specificity of MGP2-10 to tsetse and their critical role during lactation

Guaifenesin stone matrix proteomics: a protocol for identifying proteins critical to stone formation.

PubMed

Kolbach-Mandel, A M; Mandel, N S; Cohen, S R; Kleinman, J G; Ahmed, F; Mandel, I C; Wesson, J A

2017-04-01

Drug-related kidney stones are a diagnostic problem, since they contain a large matrix (protein) fraction and are frequently incorrectly identified as matrix stones. A urine proteomics study patient produced a guaifenesin stone during her participation, allowing us to both correctly diagnose her disease and identify proteins critical to this drug stone-forming process. The patient provided three random midday urine samples for proteomics studies; one of which contained stone-like sediment with two distinct fractions. These solids were characterized with optical microscopy and Fourier transform infrared spectroscopy. Immunoblotting and quantitative mass spectrometry were used to quantitatively identify the proteins in urine and stone matrix. Infrared spectroscopy showed that the sediment was 60 % protein and 40 % guaifenesin and its metabolite guaiacol. Of the 156 distinct proteins identified in the proteomic studies, 49 were identified in the two stone-components with approximately 50 % of those proteins also found in this patient's urine. Many proteins observed in this drug-related stone have also been reported in proteomic matrix studies of uric acid and calcium containing stones. More importantly, nine proteins were highly enriched and highly abundant in the stone matrix and 8 were reciprocally depleted in urine, suggesting a critical role for these proteins in guaifenesin stone formation. Accurate stone analysis is critical to proper diagnosis and treatment of kidney stones. Many matrix proteins were common to all stone types, but likely not related to disease mechanism. This protocol defined a small set of proteins that were likely critical to guaifenesin stone formation based on their high enrichment and high abundance in stone matrix, and it should be applied to all stone types.

Identifying potential markers in Breast Cancer subtypes using plasma label-free proteomics.

PubMed

Corrêa, Stephany; Panis, Carolina; Binato, Renata; Herrera, Ana Cristina; Pizzatti, Luciana; Abdelhay, Eliana

2017-01-16

Breast Cancer (BC) is the most common neoplasia among women and has a high mortality rate worldwide. Over the past several decades, increasing molecular knowledge of BC has resulted in its stratification into 4 major molecular subtypes according to hormonal receptor expression. Unfortunately, although the data accumulated thus far has improved BC prognosis and treatment, there have been few achievements in its diagnosis. In this study, we applied a Label-free Nano-LC/MSMS approach to reveal systemic molecular features and possible plasma markers for BC patients. Compared to healthy control plasma donors, we identified 191, 166, 182, and 186 differentially expressed proteins in the Luminal, Lumina-HER2, HER2, and TN subtypes. In silico analysis demonstrated an overall downregulation of cellular basal machinery and, more importantly, brought new focus to the known pathways and signaling molecules in BC that are related to immune system alterations. Moreover, using western blot analysis, we verified high levels of BCAS3, IRX1, IRX4 and IRX5 in BC plasma samples, thus highlighting the potential use of plasma proteomics in investigations into cancer biomarkers. The results of this study provide new insight into Breast Cancer (BC). We determined the plasma proteomic profile of BC subtypes. Furthermore, we report that the signaling pathways correlating with late processes in BC already exhibit plasma alterations in less aggressive subtypes. Additionally, we validated the high levels of particular proteins in patient samples, which suggests the use of these proteins as potential disease markers.

Identifying Unstable Regions of Proteins Involved in Misfolding Diseases

NASA Astrophysics Data System (ADS)

Guest, Will; Cashman, Neil; Plotkin, Steven

2009-05-01

Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and all-atoms molecular dynamics. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

Applications of Venom Proteins as Potential Anticancer agents.

PubMed

Ejaz, Samina; Hashmi, Fatima Bashir; Malik, Waqas Nazir; Ashraf, Muhammad; Nasim, Faiz Ul-Hassan; Iqbal, Muhammad

2018-06-13

Venoms, the secretions of venomous animals, are conventionally thought to be the source of toxic substances though the views about venoms in the recent era have been changed. Venoms are the proven source of many biologically and pharmacologically important useful molecules. Bioactive components present in different venoms are mainly proteins and peptides either enzymatic or non-enzymatic which have tremendous therapeutic potential and are being used for the treatment of variety of diseases including cancer. Many venoms proteins and peptides have been reported as potential anticancer agents. Venom proteins kill cancer cells through a variety of mechanisms which induce apoptosis and ultimately lead to cell death. Therefore, the understanding regarding sources and classification of venoms, biological role of venomous proteins, their anticancer potential and mechanisms to suppress/kill cancer cells needs to be addressed. The present review is an attempt to highlight the reported work and develop strategies to answer the key questions regarding the use of venomous proteins as therapeutic agents. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Methods of identifying potential vanpool riders.

DOT National Transportation Integrated Search

1977-01-01

Identifying potential vanpool riders and matching them to form pools are fundamental tasks in the initiation of a vanpool program. The manner in which these tasks are done will determine the costs and benefits of the program. This report presents the...

Essential multimeric enzymes in kinetoplastid parasites: A host of potentially druggable protein-protein interactions.

PubMed

Wachsmuth, Leah M; Johnson, Meredith G; Gavenonis, Jason

2017-06-01

Parasitic diseases caused by kinetoplastid parasites of the genera Trypanosoma and Leishmania are an urgent public health crisis in the developing world. These closely related species possess a number of multimeric enzymes in highly conserved pathways involved in vital functions, such as redox homeostasis and nucleotide synthesis. Computational alanine scanning of these protein-protein interfaces has revealed a host of potentially ligandable sites on several established and emerging anti-parasitic drug targets. Analysis of interfaces with multiple clustered hotspots has suggested several potentially inhibitable protein-protein interactions that may have been overlooked by previous large-scale analyses focusing solely on secondary structure. These protein-protein interactions provide a promising lead for the development of new peptide and macrocycle inhibitors of these enzymes.

Bioinformatics analysis identifies several intrinsically disordered human E3 ubiquitin-protein ligases.

PubMed

Boomsma, Wouter; Nielsen, Sofie V; Lindorff-Larsen, Kresten; Hartmann-Petersen, Rasmus; Ellgaard, Lars

2016-01-01

The ubiquitin-proteasome system targets misfolded proteins for degradation. Since the accumulation of such proteins is potentially harmful for the cell, their prompt removal is important. E3 ubiquitin-protein ligases mediate substrate ubiquitination by bringing together the substrate with an E2 ubiquitin-conjugating enzyme, which transfers ubiquitin to the substrate. For misfolded proteins, substrate recognition is generally delegated to molecular chaperones that subsequently interact with specific E3 ligases. An important exception is San1, a yeast E3 ligase. San1 harbors extensive regions of intrinsic disorder, which provide both conformational flexibility and sites for direct recognition of misfolded targets of vastly different conformations. So far, no mammalian ortholog of San1 is known, nor is it clear whether other E3 ligases utilize disordered regions for substrate recognition. Here, we conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology of their ordered regions, and did not capture the unique disorder patterns that encode the functional mechanism of San1. However, by searching specifically for key features of the San1 sequence, such as long regions of intrinsic disorder embedded with short stretches predicted to be suitable for substrate interaction, we identified several E3 ligases with these characteristics. Our initial analysis revealed that another remarkable trait of San1 is shared with several candidate E3 ligases: long stretches of complete lysine suppression, which in San1 limits auto-ubiquitination. We encode these characteristic features into a San1 similarity-score, and present a set of proteins that are plausible candidates as San1 counterparts in humans. In conclusion, our work indicates that San1 is

Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems

PubMed Central

MacPherson, Jamie I.; Dickerson, Jonathan E.; Pinney, John W.; Robertson, David L.

2010-01-01

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection. PMID:20686668

Identification of snake bradykinin-potentiating peptides (BPPs)-simile sequences in rat brain--Potential BPP-like precursor protein?

PubMed

Campeiro, Joana D'Arc; Neshich, Izabella P; Sant'Anna, Osvaldo A; Lopes, Robson; Ianzer, Danielle; Assakura, Marina T; Neshich, Goran; Hayashi, Mirian A F

2015-08-01

Bradykinin-potentiating peptides (BPPs) from the South American pit viper snake venom were the first natural inhibitors of the human angiotensin I-converting enzyme (ACE) described. The pioneer characterization of the BPPs precursor from the snake venom glands by our group showed for the first time the presence of the C-type natriuretic peptide (CNP) in this same viper precursor protein. The confirmation of the BPP/CNP expression in snake brain regions correlated with neuroendocrine functions stimulated us to pursue the physiological correlates of these vasoactive peptides in mammals. Notably, several snake toxins were shown to have endogenous physiological correlates in mammals. In the present work, we expressed in bacteria the BPPs domain of the snake venom gland precursor protein, and this purified recombinant protein was used to raise specific polyclonal anti-BPPs antibodies. The correspondent single protein band immune-recognized in adult rat brain cytosol was isolated by 2D-SDS/PAGE and/or HPLC, before characterization by MS fingerprint analysis, which identified this protein as superoxide dismutase (SOD, EC 1.15.1.1), a classically known enzyme with antioxidant activity and important roles in the blood pressure modulation. In silico analysis showed the exposition of the BPP-like peptide sequences on the surface of the 3D structure of rat SOD. These peptides were chemically synthesized to show the BPP-like biological activities in ex vivo and in vivo pharmacological bioassays. Taken together, our data suggest that SOD protein have the potential to be a source for putative BPP-like bioactive peptides, which once released may contribute to the blood pressure control in mammals. Copyright © 2015 Elsevier Inc. All rights reserved.

EVALLER: a web server for in silico assessment of potential protein allergenicity

PubMed Central

Barrio, Alvaro Martinez; Soeria-Atmadja, Daniel; Nistér, Anders; Gustafsson, Mats G.; Hammerling, Ulf; Bongcam-Rudloff, Erik

2007-01-01

Bioinformatics testing approaches for protein allergenicity, involving amino acid sequence comparisons, have evolved appreciably over the last several years to increased sophistication and performance. EVALLER, the web server presented in this article is based on our recently published ‘Detection based on Filtered Length-adjusted Allergen Peptides’ (DFLAP) algorithm, which affords in silico determination of potential protein allergenicity of high sensitivity and excellent specificity. To strengthen bioinformatics risk assessment in allergology EVALLER provides a comprehensive outline of its judgment on a query protein's potential allergenicity. Each such textual output incorporates a scoring figure, a confidence numeral of the assignment and information on high- or low-scoring matches to identified allergen-related motifs, including their respective location in accordingly derived allergens. The interface, built on a modified Perl Open Source package, enables dynamic and color-coded graphic representation of key parts of the output. Moreover, pertinent details can be examined in great detail through zoomed views. The server can be accessed at http://bioinformatics.bmc.uu.se/evaller.html. PMID:17537818

Unique secreted–surface protein complex of Lactobacillus rhamnosus, identified by phage display

PubMed Central

Gagic, Dragana; Wen, Wesley; Collett, Michael A; Rakonjac, Jasna

2013-01-01

Proteins are the most diverse structures on bacterial surfaces; hence, they are candidates for species- and strain-specific interactions of bacteria with the host, environment, and other microorganisms. Genomics has decoded thousands of bacterial surface and secreted proteins, yet the function of most cannot be predicted because of the enormous variability and a lack of experimental data that would allow deduction of function through homology. Here, we used phage display to identify a pair of interacting extracellular proteins in the probiotic bacterium Lactobacillus rhamnosus HN001. A secreted protein, SpcA, containing two bacterial immunoglobulin-like domains type 3 (Big-3) and a domain distantly related to plant pathogen response domain 1 (PR-1-like) was identified by screening of an L. rhamnosus HN001 library using HN001 cells as bait. The SpcA-“docking” protein, SpcB, was in turn detected by another phage display library screening, using purified SpcA as bait. SpcB is a 3275-residue cell-surface protein that contains general features of large glycosylated Serine-rich adhesins/fibrils from gram-positive bacteria, including the hallmark signal sequence motif KxYKxGKxW. Both proteins are encoded by genes within a L. rhamnosus-unique gene cluster that distinguishes this species from other lactobacilli. To our knowledge, this is the first example of a secreted-docking protein pair identified in lactobacilli. PMID:23233310

Identifying Protein-protein Interaction in Drosophila Adult Heads by Tandem Affinity Purification (TAP)

PubMed Central

Tian, Xiaolin; Zhu, Mingwei; Li, Long; Wu, Chunlai

2013-01-01

Genetic screens conducted using Drosophila melanogaster (fruit fly) have made numerous milestone discoveries in the advance of biological sciences. However, the use of biochemical screens aimed at extending the knowledge gained from genetic analysis was explored only recently. Here we describe a method to purify the protein complex that associates with any protein of interest from adult fly heads. This method takes advantage of the Drosophila GAL4/UAS system to express a bait protein fused with a Tandem Affinity Purification (TAP) tag in fly neurons in vivo, and then implements two rounds of purification using a TAP procedure similar to the one originally established in yeast1 to purify the interacting protein complex. At the end of this procedure, a mixture of multiple protein complexes is obtained whose molecular identities can be determined by mass spectrometry. Validation of the candidate proteins will benefit from the resource and ease of performing loss-of-function studies in flies. Similar approaches can be applied to other fly tissues. We believe that the combination of genetic manipulations and this proteomic approach in the fly model system holds tremendous potential for tackling fundamental problems in the field of neurobiology and beyond. PMID:24335807

A screen of cell-surface molecules identifies leucine-rich repeat proteins as key mediators of synaptic target selection in the Drosophila neuromuscular system

PubMed Central

Kurusu, Mitsuhiko; Cording, Amy; Taniguchi, Misako; Menon, Kaushiki; Suzuki, Emiko; Zinn, Kai

2008-01-01

Summary In Drosophila embryos and larvae, a small number of identified motor neurons innervate body wall muscles in a highly stereotyped pattern. Although genetic screens have identified many proteins that are required for axon guidance and synaptogenesis in this system, little is known about the mechanisms by which muscle fibers are defined as targets for specific motor axons. To identify potential target labels, we screened 410 genes encoding cell-surface and secreted proteins, searching for those whose overexpression on all muscle fibers causes motor axons to make targeting errors. Thirty such genes were identified, and a number of these were members of a large gene family encoding proteins whose extracellular domains contain leucine-rich repeat (LRR) sequences, which are protein interaction modules. By manipulating gene expression in muscle 12, we showed that four LRR proteins participate in the selection of this muscle as the appropriate synaptic target for the RP5 motor neuron. PMID:18817735

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

PubMed Central

Antrobus, Robin; Hirst, Jennifer; Bhumbra, Gary S.; Kozik, Patrycja; Jackson, Lauren P.; Sahlender, Daniela A.

2012-01-01

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a “profiling” cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions. PMID:22472443

Strategy to Identify and Test Putative Light-Sensitive Non-Opsin G-Protein-Coupled Receptors: A Case Study.

PubMed

Faggionato, Davide; Serb, Jeanne M

2017-08-01

The rise of high-throughput RNA sequencing (RNA-seq) and de novo transcriptome assembly has had a transformative impact on how we identify and study genes in the phototransduction cascade of non-model organisms. But the advantage provided by the nearly automated annotation of RNA-seq transcriptomes may at the same time hinder the possibility for gene discovery and the discovery of new gene functions. For example, standard functional annotation based on domain homology to known protein families can only confirm group membership, not identify the emergence of new biochemical function. In this study, we show the importance of developing a strategy that circumvents the limitations of semiautomated annotation and apply this workflow to photosensitivity as a means to discover non-opsin photoreceptors. We hypothesize that non-opsin G-protein-coupled receptor (GPCR) proteins may have chromophore-binding lysines in locations that differ from opsin. Here, we provide the first case study describing non-opsin light-sensitive GPCRs based on tissue-specific RNA-seq data of the common bay scallop Argopecten irradians (Lamarck, 1819). Using a combination of sequence analysis and three-dimensional protein modeling, we identified two candidate proteins. We tested their photochemical properties and provide evidence showing that these two proteins incorporate 11-cis and/or all-trans retinal and react to light photochemically. Based on this case study, we demonstrate that there is potential for the discovery of new light-sensitive GPCRs, and we have developed a workflow that starts from RNA-seq assemblies to the discovery of new non-opsin, GPCR-based photopigments.

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

NASA Technical Reports Server (NTRS)

Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

1995-01-01

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

PubMed

Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

2010-10-01

The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of <3%, we identified 111 candidates from conditioned medium, including 44 proteins that have signal peptides or are described as secreted proteins in the UniProt database. As validation, we confirmed that one of these proteins, insulin-like growth factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

Proteomics informed by transcriptomics identifies novel secreted proteins in Dermacentor andersoni saliva

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mudenda, Lwiindi; Aguilar Pierle, Sebastian; Turse, Joshua E.

2014-08-07

Dermacentor andersoni, known as the Rocky Mountain wood tick, is found in the western United States and transmits pathogens that cause diseases of veterinary and public health importance including Rocky Mountain spotted fever, tularemia, Colorado tick fever and bovine anaplasmosis. Tick saliva is known to modulate both innate and acquired immune responses, enabling ticks to feed for several days without detection. During feeding ticks subvert host defences such as hemostasis and inflammation, which would otherwise result in coagulation, wound repair and rejection of the tick. Molecular characterization of the proteins and pharmacological molecules secreted in tick saliva offers an opportunitymore » to develop tick vaccines as an alternative to the use of acaricides, as well as new anti-inflammatory drugs. We performed proteomics informed by transcriptomics to identify D. andersoni saliva proteins that are secreted during feeding. The transcript data generated a database of 21,797 consensus sequences, which we used to identify 677 proteins secreted in the saliva of D. andersoni ticks fed for 2 and 5 days, following proteomic investigations of whole saliva using mass spectrometry. Salivary gland transcript levels of unfed ticks were compared with 2 and 5 day fed ticks to identify genes upregulated early during tick feeding. We cross-referenced the proteomic data with the transcriptomic data to identify 157 proteins of interest for immunomodulation and blood feeding. Proteins of unknown function as well as known immunomodulators were identified.« less

Mammalian plasma membrane proteins as potential biomarkers and drug targets.

PubMed

Rucevic, Marijana; Hixson, Douglas; Josic, Djuro

2011-06-01

Defining the plasma membrane proteome is crucial to understand the role of plasma membrane in fundamental biological processes. Change in membrane proteins is one of the first events that take place under pathological conditions, making plasma membrane proteins a likely source of potential disease biomarkers with prognostic or diagnostic potential. Membrane proteins are also potential targets for monoclonal antibodies and other drugs that block receptors or inhibit enzymes essential to the disease progress. Despite several advanced methods recently developed for the analysis of hydrophobic proteins and proteins with posttranslational modifications, integral membrane proteins are still under-represented in plasma membrane proteome. Recent advances in proteomic investigation of plasma membrane proteins, defining their roles as diagnostic and prognostic disease biomarkers and as target molecules in disease treatment, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics

PubMed Central

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients’ saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects (p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity. PMID:28326926

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

PubMed

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

Juvenile hormone-binding proteins of Melanoplus bivittatus identified by EFDA photoaffinity labeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winder, B.S.

1988-01-01

Proteins that bind juvenile hormone in the hemolymph and fat body of the grasshopper, Melanoplus bivittatus were identified by photoaffinity labeling with radiolabeled epoxyfarnesyl diazoacetate ({sup 3}H-EFDA), and were characterized by electrophoretic analysis. A protocol was developed which allowed detection of {sup 3}H-EFDA that was covalently linked to proteins upon exposure to ultraviolet light at 254 nm. Quantification of protein-linked {sup 3}H-EFDA by liquid scintillation spectrometry took advantage of the differential solubility of unlinked {sup 3}H-EFDA in toluene alone, and of the protein-linked {sup 3}H-EFDA in toluene plus the detergent, Triton X-100. Competition between EFDA and juvenile hormone (JH) formore » binding to JH-specific binding sites was measured by hydroxyapatite protein binding assays in the presence of radiolabeled JH or EFDA and competing non-radiolabeled hormone. The protein-linked EFDA was detected on fluorograms of SDS or nondenaturing polyacrylamide gels (PAGE), and by liquid scintillation spectrometry of membranes to which the proteins had been electrophoretically transferred. Proteins which specifically bound JH were identified by photolabeling proteins in the presence and absence of nonlabeled JH-III.« less

Proteomic analysis of cerebrospinal fluid from children with central nervous system tumors identifies candidate proteins relating to tumor metastatic spread.

PubMed

Spreafico, Filippo; Bongarzone, Italia; Pizzamiglio, Sara; Magni, Ruben; Taverna, Elena; De Bortoli, Maida; Ciniselli, Chiara M; Barzanò, Elena; Biassoni, Veronica; Luchini, Alessandra; Liotta, Lance A; Zhou, Weidong; Signore, Michele; Verderio, Paolo; Massimino, Maura

2017-07-11

Central nervous system (CNS) tumors are the most common solid tumors in childhood. Since the sensitivity of combined cerebrospinal fluid (CSF) cytology and radiological neuroimaging in detecting meningeal metastases remains relatively low, we sought to characterize the CSF proteome of patients with CSF tumors to identify biomarkers predictive of metastatic spread. CSF samples from 27 children with brain tumors and 13 controls (extra-CNS non-Hodgkin lymphoma) were processed using core-shell hydrogel nanoparticles, and analyzed with reverse-phase liquid chromatography/electrospray tandem mass spectrometry (LC-MS/MS). Candidate proteins were identified with Fisher's exact test and/or a univariate logistic regression model. Reverse phase protein array (RPPA), Western blot (WB), and ELISA were used in the training set and in an independent set of CFS samples (60 cases, 14 controls) to validate our discovery findings. Among the 558 non-redundant proteins identified by LC-MS/MS, 147 were missing from the CSF database at http://www.biosino.org. Fourteen of the 26 final top-candidate proteins were chosen for validation with WB, RPPA and ELISA methods. Six proteins (type 1 collagen, insulin-like growth factor binding protein 4, procollagen C-endopeptidase enhancer 1, glial cell-line derived neurotrophic factor receptor α2, inter-alpha-trypsin inhibitor heavy chain 4, neural proliferation and differentiation control protein-1) revealed the ability to discriminate metastatic cases from controls. Combining a unique dataset of CSFs from pediatric CNS tumors with a novel enabling nanotechnology led us to identify CSF proteins potentially related to metastatic status.

A New Scheme to Characterize and Identify Protein Ubiquitination Sites.

PubMed

Nguyen, Van-Nui; Huang, Kai-Yao; Huang, Chien-Hsun; Lai, K Robert; Lee, Tzong-Yi

2017-01-01

Protein ubiquitination, involving the conjugation of ubiquitin on lysine residue, serves as an important modulator of many cellular functions in eukaryotes. Recent advancements in proteomic technology have stimulated increasing interest in identifying ubiquitination sites. However, most computational tools for predicting ubiquitination sites are focused on small-scale data. With an increasing number of experimentally verified ubiquitination sites, we were motivated to design a predictive model for identifying lysine ubiquitination sites for large-scale proteome dataset. This work assessed not only single features, such as amino acid composition (AAC), amino acid pair composition (AAPC) and evolutionary information, but also the effectiveness of incorporating two or more features into a hybrid approach to model construction. The support vector machine (SVM) was applied to generate the prediction models for ubiquitination site identification. Evaluation by five-fold cross-validation showed that the SVM models learned from the combination of hybrid features delivered a better prediction performance. Additionally, a motif discovery tool, MDDLogo, was adopted to characterize the potential substrate motifs of ubiquitination sites. The SVM models integrating the MDDLogo-identified substrate motifs could yield an average accuracy of 68.70 percent. Furthermore, the independent testing result showed that the MDDLogo-clustered SVM models could provide a promising accuracy (78.50 percent) and perform better than other prediction tools. Two cases have demonstrated the effective prediction of ubiquitination sites with corresponding substrate motifs.

A novel approach to identify genes that determine grain protein deviation in cereals.

PubMed

Mosleth, Ellen F; Wan, Yongfang; Lysenko, Artem; Chope, Gemma A; Penson, Simon P; Shewry, Peter R; Hawkesford, Malcolm J

2015-06-01

Grain yield and protein content were determined for six wheat cultivars grown over 3 years at multiple sites and at multiple nitrogen (N) fertilizer inputs. Although grain protein content was negatively correlated with yield, some grain samples had higher protein contents than expected based on their yields, a trait referred to as grain protein deviation (GPD). We used novel statistical approaches to identify gene transcripts significantly related to GPD across environments. The yield and protein content were initially adjusted for nitrogen fertilizer inputs and then adjusted for yield (to remove the negative correlation with protein content), resulting in a parameter termed corrected GPD. Significant genetic variation in corrected GPD was observed for six cultivars grown over a range of environmental conditions (a total of 584 samples). Gene transcript profiles were determined in a subset of 161 samples of developing grain to identify transcripts contributing to GPD. Principal component analysis (PCA), analysis of variance (ANOVA) and means of scores regression (MSR) were used to identify individual principal components (PCs) correlating with GPD alone. Scores of the selected PCs, which were significantly related to GPD and protein content but not to the yield and significantly affected by cultivar, were identified as reflecting a multivariate pattern of gene expression related to genetic variation in GPD. Transcripts with consistent variation along the selected PCs were identified by an approach hereby called one-block means of scores regression (one-block MSR). © 2014 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

The cellular prion protein identifies bipotential cardiomyogenic progenitors.

PubMed

Hidaka, Kyoko; Shirai, Manabu; Lee, Jong-Kook; Wakayama, Takanari; Kodama, Itsuo; Schneider, Michael D; Morisaki, Takayuki

2010-01-08

The paucity of specific surface markers for cardiomyocytes and their progenitors has impeded the development of embryonic or pluripotent stem cell-based transplantation therapy. Identification of relevant surface markers may also enhance our understanding of the mechanisms underlying differentiation. Here, we show that cellular prion protein (PrP) serves as an effective surface marker for isolating nascent cardiomyocytes as well as cardiomyogenic progenitors. Embryonic stem (or embryo-derived) cells were analyzed using flow cytometry to detect surface expression of PrP and intracellular myosin heavy chain (Myhc) proteins. Sorted cells were then analyzed for their differentiation potential. PrP+ cells from beating embryoid bodies (EBs) frequently included nascent Myhc+ cardiomyocytes. Cultured PrP+ cells further differentiated, giving rise to cardiac troponin I+ definitive cardiomyocytes with either an atrial or a ventricular identity. These cells were electrophysiologically functional and able to survive in vivo after transplantation. Combining PrP with a second marker, platelet-derived growth factor receptor (PDGFR)alpha, enabled us to identify an earlier cardiomyogenic population from prebeating EBs, the PrP+PDGFRalpha+ (PRa) cells. The Myhc- PRa cells expressed cardiac transcription factors, such as Nkx2.5, T-box transcription factor 5, and Isl1 (islet LIM homeobox 1), although they were not completely committed. In mouse embryos, PRa cells in cardiac crescent at the 1 to 2 somite stage were Myhc+, whereas they were Myhc- at headfold stages. PRa cells clonally expanded in methlycellulose cultures. Furthermore, single Myhc- PRa cell-derived colonies contained both cardiac and smooth muscle cells. Thus, PrP demarcates a population of bipotential cardiomyogenic progenitor cells that can differentiate into cardiac or smooth muscle cells.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2011 CFR

2011-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2013 CFR

2013-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2014 CFR

2014-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2012 CFR

2012-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

40 CFR 174.529 - Bacillus thuringiensis modified Cry1Ab protein as identified under OECD Unique Identifier SYN...

Code of Federal Regulations, 2010 CFR

2010-07-01

... protein as identified under OECD Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement... Unique Identifier SYN-IR67B-1 in cotton; exemption from the requirement of a tolerance. Residues of... exempt from the requirement of a tolerance when used as a plant-incorporated protectant in cotton; cotton...

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

PubMed

Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction

Dissecting protein function: an efficient protocol for identifying separation-of-function mutations that encode structurally stable proteins.

PubMed

Lubin, Johnathan W; Rao, Timsi; Mandell, Edward K; Wuttke, Deborah S; Lundblad, Victoria

2013-03-01

Mutations that confer the loss of a single biochemical property (separation-of-function mutations) can often uncover a previously unknown role for a protein in a particular biological process. However, most mutations are identified based on loss-of-function phenotypes, which cannot differentiate between separation-of-function alleles vs. mutations that encode unstable/unfolded proteins. An alternative approach is to use overexpression dominant-negative (ODN) phenotypes to identify mutant proteins that disrupt function in an otherwise wild-type strain when overexpressed. This is based on the assumption that such mutant proteins retain an overall structure that is comparable to that of the wild-type protein and are able to compete with the endogenous protein (Herskowitz 1987). To test this, the in vivo phenotypes of mutations in the Est3 telomerase subunit from Saccharomyces cerevisiae were compared with the in vitro secondary structure of these mutant proteins as analyzed by circular-dichroism spectroscopy, which demonstrates that ODN is a more sensitive assessment of protein stability than the commonly used method of monitoring protein levels from extracts. Reverse mutagenesis of EST3, which targeted different categories of amino acids, also showed that mutating highly conserved charged residues to the oppositely charged amino acid had an increased likelihood of generating a severely defective est3(-) mutation, which nevertheless encoded a structurally stable protein. These results suggest that charge-swap mutagenesis directed at a limited subset of highly conserved charged residues, combined with ODN screening to eliminate partially unfolded proteins, may provide a widely applicable and efficient strategy for generating separation-of-function mutations.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

PubMed

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Identify High-Quality Protein Structural Models by Enhanced K-Means

PubMed Central

Li, Haiou; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squared distance to optimize the initial centroids (K-means++). Our results showed that SK-means and K-means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K-means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK-means and K-means++ demonstrated substantial improvements relative to results from SPICKER and classical K-means. PMID:28421198

Affinity resins as new tools for identifying target proteins of ascorbic acid.

PubMed

Iwaoka, Yuji; Nishino, Kohei; Ishikawa, Takahiro; Ito, Hideyuki; Sawa, Yoshihiro; Tai, Akihiro

2018-02-12

l-Ascorbic acid (AA) has diverse physiological functions, but little is known about the functional mechanisms of AA. In this study, we synthesized two types of affinity resin on which AA is immobilized in a stable form to identify new AA-targeted proteins, which can provide important clues for elucidating unknown functional mechanisms of AA. To our knowledge, an affinity resin on which AA as a ligand is immobilized has not been prepared, because AA is very unstable and rapidly degraded in an aqueous solution. By using the affinity resins, cytochrome c (cyt c) was identified as an AA-targeted protein, and we showed that oxidized cyt c exhibits specific affinity for AA. These results suggest that two kinds of AA-affinity resin can be powerful tools to identify new target proteins of AA.

Small-molecule inhibitors of phosphatidylcholine transfer protein/StarD2 identified by high-throughput screening.

PubMed

Wagle, Neil; Xian, Jun; Shishova, Ekaterina Y; Wei, Jie; Glicksman, Marcie A; Cuny, Gregory D; Stein, Ross L; Cohen, David E

2008-12-01

Phosphatidylcholine transfer protein (PC-TP, also referred to as StarD2) is a highly specific intracellular lipid-binding protein that catalyzes the transfer of phosphatidylcholines between membranes in vitro. Recent studies have suggested that PC-TP in vivo functions to regulate fatty acid and glucose metabolism, possibly via interactions with selected other proteins. To begin to address the relationship between activity in vitro and biological function, we undertook a high-throughput screen to identify small-molecule inhibitors of the phosphatidylcholine transfer activity of PC-TP. After adapting a fluorescence quench assay to measure phosphatidylcholine transfer activity, we screened 114,752 compounds of a small-molecule library. The high-throughput screen identified 14 potential PC-TP inhibitors. Of these, 6 compounds exhibited characteristics consistent with specific inhibition of PC-TP activity, with IC(50) values that ranged from 4.1 to 95.0muM under conditions of the in vitro assay. These compounds should serve as valuable reagents to elucidate the biological function of PC-TP. Because mice with homozygous disruption of the PC-TP gene (Pctp) are sensitized to insulin action and relatively resistant to the development of atherosclerosis, these inhibitors may also prove to be of value in the management of diabetes and atherosclerotic cardiovascular diseases.

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

Method for early detection of infectious mononucleosis by identifying inmono proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willard, K. E.

1984-10-02

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.

Method for early detection of infectious mononucleosis by identifying Inmono proteins

DOEpatents

Willard, Karen E.

1984-01-01

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.

Integrating virtual screening and biochemical experimental approach to identify potential anti-cancer agents from drug databank.

PubMed

Deka, Suman Jyoti; Roy, Ashalata; Manna, Debasis; Trivedi, Vishal

2018-06-01

Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues. Molecular dynamics simulation of PKC-Cinnarizine complex at different temperatures (300, 325, 350, 375, and 400[Formula: see text]K) confirms that Cinnarizine fits nicely into the C2 domain and forms a stable complex. The drug Cinnarizine was found to bind PKC with a dissociation constant Kd of [Formula: see text]M. The breast cancer cells stimulated with Cinnarizine causes translocation of PKC-[Formula: see text] to the plasma membrane as revealed by immunoblotting and immunofluorescence studies. Cinnarizine also dose dependently reduced the viability of MDAMB-231 and MCF-7 breast cancer cells with an IC[Formula: see text] of [Formula: see text] and [Formula: see text]g/mL, respectively. It is due to the disturbance of cell cycle of breast cancer cells with reduction of S-phase and accumulation of cells in G1-phase. It disturbs mitochondrial membrane potentials to release cytochrome C into the cytosol and activates caspase-3 to induce apoptosis in cancer cells. The cell death was due to induction of apoptosis involving mitochondrial pathway. Hence, the current study has assigned an additional role to Cinnarizine as an activator of PKC and potentials of the approach to identify new molecules for anti-cancer therapy. Thus, in silico screening along with biochemical experimentation is a robust approach to assign additional roles to the drugs present in the databank for anti-cancer therapy.

Application of a proteomic approach to identify proteins associated with primary graft non-function after liver transplantation.

PubMed

Kornasiewicz, Oskar; Bojarczuk, Kamil; Bugajski, Marek; Golab, Jakub; Krawczyk, Marek

2012-10-01

Primary graft non-function (PNF) is a rare, life-threatening complication of liver transplantation. Increasing use of extended criteria donor pools and high-risk recipients seem to influence the incidence of PNF. Primary failure is associated with high patient morbidity and inferior graft survival. The only available treatment for PNF is emergency hepatic retransplantation, which is also correlated with significant morbidity and mortality. Therefore, researchers are working to identify risk factors of diagnostic value to prevent PNF. The current study attempted to explore liver proteomic patterns in patients with PNF. Using two-dimensional gel electrophoresis and liquid chromatography-mass spectrometry (LC-MS), we compared liver protein homogenates from 3 patients with PNF to those obtained from 6 healthy liver samples to identify potential new biomarkers of PNF. Our comparisons revealed 21 proteins with differential expression (13 upregulated and 8 downregulated). Most of these proteins are involved in energy metabolism, lipid metabolism, peptide cleavage, cell differentiation, and apoptosis. Although none of these proteins appeared more than once in separate analyses, this preliminary study shows that two-dimensional gel electrophoresis and LC-MS may allow identification of characteristic proteins to be used as biomarkers of a life-threatening complication of liver transplantation. Larger-scale analyses could improve patient care by finding suitable prognostic and therapeutic options. These data represent the first global proteomic approach to study PNF.

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

PubMed

Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi

2017-09-01

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.

Apoptosis induced by low-intensity ultrasound in vitro: Alteration of protein profile and potential molecular mechanism

NASA Astrophysics Data System (ADS)

Feng, Yi; Wan, Mingxi

2017-03-01

To analyze the potential mechanism related to the apoptosis induced by low intensity focused ultrasound, comparative proteomic method was introduced in the study. After ultrasound irradiation (3.0 W/cm2, 1 minute, 6 hours incubation post-irradiation), the human SMMC-7721 hepatocarcinoma cells were stained by trypan blue to detect the morphologic changes, and then the percentage of early apoptosis were tested by the flow cytometry with double staining of FITC-labelled Annexin V/Propidium iodide. Two-dimensional SDS polyacrylamide gel electrophoresis was used to get the protein profile and some proteins differently expressed after ultrasound irradiation were identified by MALDI-TOF mass spectrometry. It's proved early apoptosis of cells were induced by low intentisy focused ultrasound. After ultrasound irradiation, the expressing characteristics of several proteins changed, in which protein p53 and heat shock proteins are associated with apoptosis initiation. It is suggested that the low-intensity ultrasound-induced apoptotic cancer therapy has the potential application via understanding its relevant molecular signaling and key proteins. Moreover, the comparative proteomic method is proved to be useful to supply information about the protein expression to analyze the metabolic processes related to bio-effects of biomedical ultrasound.

Improved side-chain torsion potentials for the Amber ff99SB protein force field

PubMed Central

Lindorff-Larsen, Kresten; Piana, Stefano; Palmo, Kim; Maragakis, Paul; Klepeis, John L; Dror, Ron O; Shaw, David E

2010-01-01

Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations in the accuracy of the force fields used for such simulations and spurring efforts to refine these force fields. Recent modifications to the Amber and CHARMM protein force fields, for example, have improved the backbone torsion potentials, remedying deficiencies in earlier versions. Here, we further advance simulation accuracy by improving the amino acid side-chain torsion potentials of the Amber ff99SB force field. First, we used simulations of model alpha-helical systems to identify the four residue types whose rotamer distribution differed the most from expectations based on Protein Data Bank statistics. Second, we optimized the side-chain torsion potentials of these residues to match new, high-level quantum-mechanical calculations. Finally, we used microsecond-timescale MD simulations in explicit solvent to validate the resulting force field against a large set of experimental NMR measurements that directly probe side-chain conformations. The new force field, which we have termed Amber ff99SB-ILDN, exhibits considerably better agreement with the NMR data. Proteins 2010. © 2010 Wiley-Liss, Inc. PMID:20408171

Phenotypic Screening Identifies Protein Synthesis Inhibitors as H-Ras-Nanocluster-Increasing Tumor Growth Inducers.

PubMed

Najumudeen, Arafath K; Posada, Itziar M D; Lectez, Benoit; Zhou, Yong; Landor, Sebastian K-J; Fallarero, Adyary; Vuorela, Pia; Hancock, John; Abankwa, Daniel

2015-12-15

Ras isoforms H-, N-, and K-ras are each mutated in specific cancer types at varying frequencies and have different activities in cell fate control. On the plasma membrane, Ras proteins are laterally segregated into isoform-specific nanoscale signaling hubs, termed nanoclusters. As Ras nanoclusters are required for Ras signaling, chemical modulators of nanoclusters represent ideal candidates for the specific modulation of Ras activity in cancer drug development. We therefore conducted a chemical screen with commercial and in-house natural product libraries using a cell-based H-ras-nanoclustering FRET assay. Next to established Ras inhibitors, such as a statin and farnesyl-transferase inhibitor, we surprisingly identified five protein synthesis inhibitors as positive regulators. Using commonly employed cycloheximide as a representative compound, we show that protein synthesis inhibition increased nanoclustering and effector recruitment specifically of active H-ras but not of K-ras. Consistent with these data, cycloheximide treatment activated both Erk and Akt kinases and specifically promoted H-rasG12V-induced, but not K-rasG12V-induced, PC12 cell differentiation. Intriguingly, cycloheximide increased the number of mammospheres, which are enriched for cancer stem cells. Depletion of H-ras in combination with cycloheximide significantly reduced mammosphere formation, suggesting an exquisite synthetic lethality. The potential of cycloheximide to promote tumor cell growth was also reflected in its ability to increase breast cancer cell tumors grown in ovo. These results illustrate the possibility of identifying Ras-isoform-specific modulators using nanocluster-directed screening. They also suggest an unexpected feedback from protein synthesis inhibition to Ras signaling, which might present a vulnerability in certain tumor cell types.

Identifying Disease Associated miRNAs Based on Protein Domains.

PubMed

Qin, Gui-Min; Li, Rui-Yi; Zhao, Xing-Ming

2016-01-01

MicroRNAs (miRNAs) are a class of small endogenous non-coding genes, acting as regulators in the post-transcriptional processes. Recently, the miRNAs are found to be widely involved in different types of diseases. Therefore, the identification of disease associated miRNAs can help understand the mechanisms that underlie the disease and identify new biomarkers. However, it is not easy to identify the miRNAs related to diseases due to its extensive involvements in various biological processes. In this work, we present a new approach to identify disease associated miRNAs based on domains, the functional and structural blocks of proteins. The results on real datasets demonstrate that our method can effectively identify disease related miRNAs with high precision.

Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development

DTIC Science & Technology

2012-09-01

orientated immobilization of proteins,” Biotechnology Progress, 22(2), 401-405 ( 2006 ). [26] J. M. Kogot, D. A. Sarkes , I. Val-Addo et al...Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development by Joshua M. Kogot, Deborah A. Sarkes ...Peptide-protein Interactions for Smart Reagent Development Joshua M. Kogot, Deborah A. Sarkes , Dimitra N. Stratis-Cullum, and Paul M

Serum Immunoproteomics Combined With Pathological Reassessment of Surgical Specimens Identifies TCP-1ζ Autoantibody as a Potential Biomarker in Thyroid Neoplasia.

PubMed

Belousov, Pavel V; Bogolyubova, Apollinariya V; Kim, Yan S; Abrosimov, Alexander Y; Kopylov, Arthur T; Tvardovskiy, Andrey A; Lanshchakov, Kirill V; Sazykin, Alexei Y; Dvinskikh, Nina Y; Bobrovskaya, Yana I; Selivanova, Lilia S; Shilov, Evgeniy S; Schwartz, Anton M; Shebzukhov, Yuriy V; Severskaia, Natalya V; Vanushko, Vladimir E; Moshkovskii, Sergei A; Nedospasov, Sergei A; Kuprash, Dmitry V

2015-09-01

Current methods of preoperative diagnostics frequently fail to discriminate between benign and malignant thyroid neoplasms. In encapsulated follicular-patterned tumors (EnFPT), this discrimination is challenging even using histopathological analysis. Autoantibody response against tumor-associated antigens is a well-documented phenomenon with prominent diagnostic potential; however, autoantigenicity of thyroid tumors remains poorly explored. Objectives were exploration of tumor-associated antigen repertoire of thyroid tumors and identification of candidate autoantibody biomarkers capable of discrimination between benign and malignant thyroid neoplasms. Proteins isolated from FTC-133 cells were subjected to two-dimensional Western blotting using pooled serum samples of patients originally diagnosed with either papillary thyroid carcinoma (PTC) or EnFPT represented by apparently benign follicular thyroid adenomas, as well as healthy individuals. Immunoreactive proteins were identified using liquid chromatography-tandem mass-spectrometry. Pathological reassessment of EnFPT was performed applying nonconservative criteria for capsular invasion and significance of focal PTC nuclear changes (PTC-NCs). Recombinant T-complex protein 1 subunitζ (TCP-1ζ) was used to examine an expanded serum sample set of patients with various thyroid neoplasms (n = 89) for TCP-1ζ autoantibodies. All patients were included in tertiary referral centers. A protein demonstrating a distinct pattern of EnFPT-specific seroreactivity was identified as TCP-1ζ protein. A subsequent search for clinicopathological correlates of TCP-1ζ seroreactivity revealed nonclassical capsular invasion or focal PTC-NC in all TCP-1ζ antibody-positive cases. Further studies in an expanded sample set confirmed the specificity of TCP-1ζ autoantibodies to malignant EnFPT. We identified TCP-1ζ autoantibodies as a potential biomarker for presurgical discrimination between benign and malignant encapsulated follicular

Extending the essential dynamics analysis to investigate molecular properties: application to the redox potential of proteins.

PubMed

Zanetti-Polzi, Laura; Corni, Stefano; Daidone, Isabella; Amadei, Andrea

2016-07-21

Here, a methodology is proposed to investigate the collective fluctuation modes of an arbitrary set of observables, maximally contributing to the fluctuation of another functionally relevant observable. The methodology, based on the analysis of fully classical molecular dynamics (MD) simulations, exploits the essential dynamics (ED) method, originally developed to analyse the collective motions in proteins. We apply this methodology to identify the residues that are more relevant for determining the reduction potential (E(0)) of a redox-active protein. To this aim, the fluctuation modes of the single-residue electrostatic potentials mostly contributing to the fluctuations of the total electrostatic potential (the main determinant of E(0)) are investigated for wild-type azurin and two of its mutants with a higher E(0). By comparing the results here obtained with a previous study on the same systems [Zanetti-Polzi et al., Org. Biomol. Chem., 2015, 13, 11003] we show that the proposed methodology is able to identify the key sites that determine E(0). This information can be used for a general deeper understanding of the molecular mechanisms on the basis of the redox properties of the proteins under investigation, as well as for the rational design of mutants with a higher or lower E(0). From the results of the present analysis we propose a new azurin mutant that, according to our calculations, shows a further increase of E(0).

Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

PubMed

Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

2015-04-01

This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

PGPR strain Paenibacillus polymyxa SQR-21 potentially benefits watermelon growth by re-shaping root protein expression.

PubMed

E, Yaoyao; Yuan, Jun; Yang, Fang; Wang, Lei; Ma, Jinghua; Li, Jing; Pu, Xiaowei; Raza, Waseem; Huang, Qiwei; Shen, Qirong

2017-12-01

Paenibacillus polymyxa (SQR-21) is not only a plant growth-promoting rhizobacteria, but also an effective biocontrol agent against Fusarium wilt disease of watermelon. For the better understanding and clarifying the potential mechanisms of SQR-21 to improve watermelon growth and disease resistance, a split-root methodology in hydroponic and LC-MS technology with the label free method was used to analyze the key root proteins involved in watermelon metabolism and disease resistance after the inoculation of SQR-21. Out of 623 identified proteins, 119 proteins were differentially expressed when treatment (SQR-21 inoculation) and control (no bacterial inoculation) were compared. Among those, 57 and 62 proteins were up-regulated and down-regulated, respectively. These differentially expressed proteins were identified to be involved in signal transduction (ADP-ribosylation factor, phospholipase D), transport (aspartate amino-transferase), carbohydratemetabolic (glucose-6-phosphate dehydrogenase, UDP-glucose pyrophosphorylase), defense and response to stress (glutathione S-transferase, Ubiquitin-activating enzyme E1), and oxidation-reduction process (thioredoxin peroxidase, ascorbate peroxidase). The results of this study indicated that SQR-21 inoculation on the watermelon roots benefits plant by inducing the expression of several proteins involved in growth, photosynthesis, and other metabolic and physiological activities.

Immunoproteomically identified GBAA_0345, alkyl hydroperoxide reductase subunit C is a potential target for multivalent anthrax vaccine.

PubMed

Kim, Yeon Hee; Kim, Kyung Ae; Kim, Yu-Ri; Choi, Min Kyung; Kim, Hye Kyeong; Choi, Ki Ju; Chun, Jeong-Hoon; Cha, Kiweon; Hong, Kee-Jong; Lee, Na Gyong; Yoo, Cheon-Kwon; Oh, Hee-Bok; Kim, Tae Sung; Rhie, Gi-eun

2014-01-01

Anthrax is caused by the spore-forming bacterium Bacillus anthracis, which has been used as a weapon for bioterrorism. Although current vaccines are effective, they involve prolonged dose regimens and often cause adverse reactions. High rates of mortality associated with anthrax have made the development of an improved vaccine a top priority. To identify novel vaccine candidates, we applied an immunoproteomics approach. Using sera from convalescent guinea pigs or from human patients with anthrax, we identified 34 immunogenic proteins from the virulent B. anthracis H9401. To evaluate vaccine candidates, six were expressed as recombinant proteins and tested in vivo. Two proteins, rGBAA_0345 (alkyl hydroperoxide reductase subunit C) and rGBAA_3990 (malonyl CoA-acyl carrier protein transacylase), have afforded guinea pigs partial protection from a subsequent virulent-spore challenge. Moreover, combined vaccination with rGBAA_0345 and rPA (protective antigen) exhibited an enhanced ability to protect against anthrax mortality. Finally, we demonstrated that GBAA_0345 localizes to anthrax spores and bacilli. Our results indicate that rGBAA_0345 may be a potential component of a multivalent anthrax vaccine, as it enhances the efficacy of rPA vaccination. This is the first time that sera from patients with anthrax have been used to interrogate the proteome of virulent B. anthracis vegetative cells. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

PubMed

Choong, Wai-Kok; Lih, Tung-Shing Mamie; Chen, Yu-Ju; Sung, Ting-Yi

2017-12-01

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues. Therefore, we conducted a thorough comparative analysis on data sets in PeptideAtlas Tiered Human Integrated Search Proteome (THISP, 2017-03 release), including neXtProt (2017-01 release), to systematically investigate the possibility of unique peptides in missing proteins (PE2-4), unique peptides in dubious proteins, and variant peptides affected by isobaric substitutions, causing doubtful identification results. In this study, we considered 11 isobaric substitutions. From our analysis, we found <5% of the unique peptides of missing proteins and >6% of variant peptides became shared with peptides of PE1 proteins after isobaric substitutions.

Phosducin-like protein: an ethanol-responsive potential modulator of guanine nucleotide-binding protein function.

PubMed

Miles, M F; Barhite, S; Sganga, M; Elliott, M

1993-11-15

Acute and chronic exposure to ethanol produces specific changes in several signal transduction cascades. Such alterations in signaling are thought to be a crucial aspect of the central nervous system's adaptive response, which occurs with chronic exposure to ethanol. We have recently identified and isolated several genes whose expression is specifically induced by ethanol in neural cell cultures. The product of one of these genes has extensive sequence homology to phosducin, a phosphoprotein expressed in retina and pineal gland that modulates trimeric guanine nucleotide-binding protein (G protein) function by binding to G-protein beta gamma subunits. We identified from a rat brain cDNA library an isolate encoding the phosducin-like protein (PhLP), which has 41% identity and 65% amino acid homology to phosducin. PhLP cDNA is expressed in all tissues screened by RNA blot-hybridization analysis and shows marked evolutionary conservation on Southern hybridization. We have identified four forms of PhLP cDNA varying only in their 5' ends, probably due to alternative splicing. This 5'-end variation generates two predicted forms of PhLP protein that differ by 79 aa at the NH2 terminus. Treatment of NG108-15 cells for 24 hr with concentrations of ethanol seen in actively drinking alcoholics (25-100 mM) causes up to a 3-fold increase in PhLP mRNA levels. Induction of PhLP by ethanol could account for at least some of the widespread alterations in signal transduction and G-protein function that are known to occur with chronic exposure to ethanol.

A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

Proteins related to the functions of fibroblast-like synoviocytes identified by proteomic analysis.

PubMed

Zhang, Hui; Fan, Lie Ying; Zong, Ming; Sun, Li Shan; Lu, Liu

2012-01-01

It is well known that the fibroblast-like synoviocytes (FLS) play a key role in pathogenesis of rheumatoid arthritis (RA). This study was performed to separate the differentially expressed proteins of FLS from the patients with RA or osteoarthritis (OA) by two-dimensional electrophoresis (2-DE), and found proteins associated with the functions of FLS by mass spectrometry (MS). Total proteins were extracted and quantified from the primary cultured FLS from patients of RA (n=8) or OA (n=6). Proteins were separated by high-resolution 2-DE, and identified the differentially expressed proteins by MS. Western blot analyses was used to validated the expression of candidate proteins. The mRNA of these proteins was detected by semi-quantitative fluorescent PCR. There are 1147 protein spots from RA and 1324 protein spots from OA showed on 2-DE graphs, respectively. We have selected 84 protein spots for MS analysis, and 27 protein spots were successfully identified. We have found that protein isoaspartyl methyltransferase (PIMT) and pirin (iron-binding nuclear protein, PIR) with lower expression in RA, and thioredoxin 1(Trx-1) only expressed in RA may be associated with functions of FLS. Western Blot confirmed the expression of PIMT and pirin lower in RA, and Trx-1 expressed only in RA. The results of semi-quantitative fluorescent PCR are also consistent with 2-DE graphs. PIMT, pirin and Trx-1 affect the functions of FLS in some style and can be the drug targets of RA.

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins

PubMed Central

Li, Hui; Wang, Rong; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area. PMID:28744305

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

PubMed

Wang, Xiao; Li, Hui; Wang, Rong; Zhang, Qiuwen; Zhang, Weiwei; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area.

Identification of urine protein biomarkers with the potential for early detection of lung cancer.

PubMed

Zhang, Hongjuan; Cao, Jing; Li, Lin; Liu, Yanbin; Zhao, Hong; Li, Nan; Li, Bo; Zhang, Aiqun; Huang, Huanwei; Chen, She; Dong, Mengqiu; Yu, Lei; Zhang, Jian; Chen, Liang

2015-07-02

Lung cancer is the leading cause of cancer-related deaths and has an overall 5-year survival rate lower than 15%. Large-scale clinical trials have demonstrated a significant relative reduction in mortality in high-risk individuals with low-dose computed tomography screening. However, biomarkers capable of identifying the most at-risk population and detecting lung cancer before it becomes clinically apparent are urgently needed in the clinic. Here, we report the identification of urine biomarkers capable of detecting lung cancer. Using the well-characterized inducible Kras (G12D) mouse model of lung cancer, we identified alterations in the urine proteome in tumor-bearing mice compared with sibling controls. Marked differences at the proteomic level were also detected between the urine of patients and that of healthy population controls. Importantly, we identified 7 proteins commonly found to be significantly up-regulated in both tumor-bearing mice and patients. In an independent cohort, we showed that 2 of the 7 proteins were up-regulated in urine samples from lung cancer patients but not in those from controls. The kinetics of these proteins correlated with the disease state in the mouse model. These tumor biomarkers could potentially aid in the early detection of lung cancer.

Quantitative proteomics identifies 38 proteins that are differentially expressed in cucumber in response to cucumber green mottle mosaic virus infection.

PubMed

Liu, Hua-Wei; Liang, Chao-Qiong; Liu, Peng-Fei; Luo, Lai-Xin; Li, Jian-Qiang

2015-12-15

Since it was first reported in 1935, Cucumber green mottle mosaic virus (CGMMV) has become a serious pathogen in a range of cucurbit crops. The virus is generally transmitted by propagation materials, and to date no effective chemical or cultural methods of control have been developed to combat its spread. The current study presents a preliminary analysis of the pathogenic mechanisms from the perspective of protein expression levels in an infected cucumber host, with the objective of elucidating the infection process and potential strategies to reduce both the economic and yield losses associated with CGMMV. Isobaric tags for relative and absolute quantitation (iTRAQ) technology coupled with liquid chromatography-tandem mass spectrometric (LC-MS/MS) were used to identify the differentially expressed proteins in cucumber plants infected with CGMMV compared with mock-inoculated plants. The functions of the proteins were deduced by functional annotation and their involvement in metabolic processes explored by KEGG pathway analysis to identify their interactions during CGMMV infection, while their in vivo expression was further verified by qPCR. Infection by CGMMV altered both the expression level and absolute quantity of 38 proteins (fold change >0.6) in cucumber hosts. Of these, 23 were found to be up-regulated, while 15 were down-regulated. Gene ontology (GO) analysis revealed that 22 of the proteins had a combined function and were associated with molecular function (MF), biological process (BP) and cellular component (CC). Several other proteins had a dual function with 1, 7, and 2 proteins being associated with BP/CC, BP/MF, CC/MF, respectively. The remaining 3 proteins were only involved in MF. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 18 proteins that were involved in 13 separate metabolic pathways. These pathways were subsequently merged to generate three network diagrams illustrating the interactions between the different

Mitochondrial Protein Interaction Mapping Identifies Regulators of Respiratory Chain Function.

PubMed

Floyd, Brendan J; Wilkerson, Emily M; Veling, Mike T; Minogue, Catie E; Xia, Chuanwu; Beebe, Emily T; Wrobel, Russell L; Cho, Holly; Kremer, Laura S; Alston, Charlotte L; Gromek, Katarzyna A; Dolan, Brendan K; Ulbrich, Arne; Stefely, Jonathan A; Bohl, Sarah L; Werner, Kelly M; Jochem, Adam; Westphall, Michael S; Rensvold, Jarred W; Taylor, Robert W; Prokisch, Holger; Kim, Jung-Ja P; Coon, Joshua J; Pagliarini, David J

2016-08-18

Mitochondria are essential for numerous cellular processes, yet hundreds of their proteins lack robust functional annotation. To reveal functions for these proteins (termed MXPs), we assessed condition-specific protein-protein interactions for 50 select MXPs using affinity enrichment mass spectrometry. Our data connect MXPs to diverse mitochondrial processes, including multiple aspects of respiratory chain function. Building upon these observations, we validated C17orf89 as a complex I (CI) assembly factor. Disruption of C17orf89 markedly reduced CI activity, and its depletion is found in an unresolved case of CI deficiency. We likewise discovered that LYRM5 interacts with and deflavinates the electron-transferring flavoprotein that shuttles electrons to coenzyme Q (CoQ). Finally, we identified a dynamic human CoQ biosynthetic complex involving multiple MXPs whose topology we map using purified components. Collectively, our data lend mechanistic insight into respiratory chain-related activities and prioritize hundreds of additional interactions for further exploration of mitochondrial protein function. Copyright © 2016 Elsevier Inc. All rights reserved.

Genome-Wide Association Mapping Combined with Reverse Genetics Identifies New Effectors of Low Water Potential-Induced Proline Accumulation in Arabidopsis1[W][OPEN

PubMed Central

Verslues, Paul E.; Lasky, Jesse R.; Juenger, Thomas E.; Liu, Tzu-Wen; Kumar, M. Nagaraj

2014-01-01

Arabidopsis (Arabidopsis thaliana) exhibits natural genetic variation in drought response, including varying levels of proline (Pro) accumulation under low water potential. As Pro accumulation is potentially important for stress tolerance and cellular redox control, we conducted a genome-wide association (GWAS) study of low water potential-induced Pro accumulation using a panel of natural accessions and publicly available single-nucleotide polymorphism (SNP) data sets. Candidate genomic regions were prioritized for subsequent study using metrics considering both the strength and spatial clustering of the association signal. These analyses found many candidate regions likely containing gene(s) influencing Pro accumulation. Reverse genetic analysis of several candidates identified new Pro effector genes, including thioredoxins and several genes encoding Universal Stress Protein A domain proteins. These new Pro effector genes further link Pro accumulation to cellular redox and energy status. Additional new Pro effector genes found include the mitochondrial protease LON1, ribosomal protein RPL24A, protein phosphatase 2A subunit A3, a MADS box protein, and a nucleoside triphosphate hydrolase. Several of these new Pro effector genes were from regions with multiple SNPs, each having moderate association with Pro accumulation. This pattern supports the use of summary approaches that incorporate clusters of SNP associations in addition to consideration of individual SNP probability values. Further GWAS-guided reverse genetics promises to find additional effectors of Pro accumulation. The combination of GWAS and reverse genetics to efficiently identify new effector genes may be especially applicable for traits difficult to analyze by other genetic screening methods. PMID:24218491

A sequence-based hybrid predictor for identifying conformationally ambivalent regions in proteins.

PubMed

Liu, Yu-Cheng; Yang, Meng-Han; Lin, Win-Li; Huang, Chien-Kang; Oyang, Yen-Jen

2009-12-03

Proteins are dynamic macromolecules which may undergo conformational transitions upon changes in environment. As it has been observed in laboratories that protein flexibility is correlated to essential biological functions, scientists have been designing various types of predictors for identifying structurally flexible regions in proteins. In this respect, there are two major categories of predictors. One category of predictors attempts to identify conformationally flexible regions through analysis of protein tertiary structures. Another category of predictors works completely based on analysis of the polypeptide sequences. As the availability of protein tertiary structures is generally limited, the design of predictors that work completely based on sequence information is crucial for advances of molecular biology research. In this article, we propose a novel approach to design a sequence-based predictor for identifying conformationally ambivalent regions in proteins. The novelty in the design stems from incorporating two classifiers based on two distinctive supervised learning algorithms that provide complementary prediction powers. Experimental results show that the overall performance delivered by the hybrid predictor proposed in this article is superior to the performance delivered by the existing predictors. Furthermore, the case study presented in this article demonstrates that the proposed hybrid predictor is capable of providing the biologists with valuable clues about the functional sites in a protein chain. The proposed hybrid predictor provides the users with two optional modes, namely, the high-sensitivity mode and the high-specificity mode. The experimental results with an independent testing data set show that the proposed hybrid predictor is capable of delivering sensitivity of 0.710 and specificity of 0.608 under the high-sensitivity mode, while delivering sensitivity of 0.451 and specificity of 0.787 under the high-specificity mode. Though

Identifying proteins that bind to specific RNAs - focus on simple repeat expansion diseases

PubMed Central

Jazurek, Magdalena; Ciesiolka, Adam; Starega-Roslan, Julia; Bilinska, Katarzyna; Krzyzosiak, Wlodzimierz J.

2016-01-01

RNA–protein complexes play a central role in the regulation of fundamental cellular processes, such as mRNA splicing, localization, translation and degradation. The misregulation of these interactions can cause a variety of human diseases, including cancer and neurodegenerative disorders. Recently, many strategies have been developed to comprehensively analyze these complex and highly dynamic RNA–protein networks. Extensive efforts have been made to purify in vivo-assembled RNA–protein complexes. In this review, we focused on commonly used RNA-centric approaches that involve mass spectrometry, which are powerful tools for identifying proteins bound to a given RNA. We present various RNA capture strategies that primarily depend on whether the RNA of interest is modified. Moreover, we briefly discuss the advantages and limitations of in vitro and in vivo approaches. Furthermore, we describe recent advances in quantitative proteomics as well as the methods that are most commonly used to validate robust mass spectrometry data. Finally, we present approaches that have successfully identified expanded repeat-binding proteins, which present abnormal RNA–protein interactions that result in the development of many neurological diseases. PMID:27625393

Accuracy of Protein Embedding Potentials: An Analysis in Terms of Electrostatic Potentials.

PubMed

Olsen, Jógvan Magnus Haugaard; List, Nanna Holmgaard; Kristensen, Kasper; Kongsted, Jacob

2015-04-14

Quantum-mechanical embedding methods have in recent years gained significant interest and may now be applied to predict a wide range of molecular properties calculated at different levels of theory. To reach a high level of accuracy in embedding methods, both the electronic structure model of the active region and the embedding potential need to be of sufficiently high quality. In fact, failures in quantum mechanics/molecular mechanics (QM/MM)-based embedding methods have often been associated with the QM/MM methodology itself; however, in many cases the reason for such failures is due to the use of an inaccurate embedding potential. In this paper, we investigate in detail the quality of the electronic component of embedding potentials designed for calculations on protein biostructures. We show that very accurate explicitly polarizable embedding potentials may be efficiently designed using fragmentation strategies combined with single-fragment ab initio calculations. In fact, due to the self-interaction error in Kohn-Sham density functional theory (KS-DFT), use of large full-structure quantum-mechanical calculations based on conventional (hybrid) functionals leads to less accurate embedding potentials than fragment-based approaches. We also find that standard protein force fields yield poor embedding potentials, and it is therefore not advisable to use such force fields in general QM/MM-type calculations of molecular properties other than energies and structures.

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

A Target-Based Whole Cell Screen Approach To Identify Potential Inhibitors of Mycobacterium tuberculosis Signal Peptidase

PubMed Central

2016-01-01

The general secretion (Sec) pathway is a conserved essential pathway in bacteria and is the primary route of protein export across the cytoplasmic membrane. During protein export, the signal peptidase LepB catalyzes the cleavage of the signal peptide and subsequent release of mature proteins into the extracellular space. We developed a target-based whole cell assay to screen for potential inhibitors of LepB, the sole signal peptidase in Mycobacterium tuberculosis, using a strain engineered to underexpress LepB (LepB-UE). We screened 72,000 compounds against both the Lep-UE and wild-type (wt) strains. We identified the phenylhydrazone (PHY) series as having higher activity against the LepB-UE strain. We conducted a limited structure–activity relationship determination around a representative PHY compound with differential activity (MICs of 3.0 μM against the LepB-UE strain and 18 μM against the wt); several analogues were less potent against the LepB overexpressing strain. A number of chemical modifications around the hydrazone moiety resulted in improved potency. Inhibition of LepB activity was observed for a number of compounds in a biochemical assay using cell membrane fraction derived from M. tuberculosis. Compounds did not increase cell permeability, dissipate membrane potential, or inhibit an unrelated mycobacterial enzyme, suggesting a specific mode of action related to the LepB secretory mechanism. PMID:27642770

Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.

Recombinant Protein Truncation Strategy for Inducing Bactericidal Antibodies to the Macrophage Infectivity Potentiator Protein of Neisseria meningitidis and Circumventing Potential Cross-Reactivity with Human FK506-Binding Proteins

PubMed Central

Bielecka, Magdalena K.; Devos, Nathalie; Gilbert, Mélanie; Hung, Miao-Chiu; Weynants, Vincent; Heckels, John E.

2014-01-01

A recombinant macrophage infectivity potentiator (rMIP) protein of Neisseria meningitidis induces significant serum bactericidal antibody production in mice and is a candidate meningococcal vaccine antigen. However, bioinformatics analysis of MIP showed some amino acid sequence similarity to human FK506-binding proteins (FKBPs) in residues 166 to 252 located in the globular domain of the protein. To circumvent the potential concern over generating antibodies that could recognize human proteins, we immunized mice with recombinant truncated type I rMIP proteins that lacked the globular domain and the signal leader peptide (LP) signal sequence (amino acids 1 to 22) and contained the His purification tag at either the N or C terminus (C-term). The immunogenicity of truncated rMIP proteins was compared to that of full (i.e., full-length) rMIP proteins (containing the globular domain) with either an N- or C-terminal His tag and with or without the LP sequence. By comparing the functional murine antibody responses to these various constructs, we determined that C-term His truncated rMIP (−LP) delivered in liposomes induced high levels of antibodies that bound to the surface of wild-type but not Δmip mutant meningococci and showed bactericidal activity against homologous type I MIP (median titers of 128 to 256) and heterologous type II and III (median titers of 256 to 512) strains, thereby providing at least 82% serogroup B strain coverage. In contrast, in constructs lacking the LP, placement of the His tag at the N terminus appeared to abrogate bactericidal activity. The strategy used in this study would obviate any potential concerns regarding the use of MIP antigens for inclusion in bacterial vaccines. PMID:25452551

Identifying different transcribed proteins in the newly described Theraphosidae Pamphobeteus verdolaga.

PubMed

Estrada-Gómez, Sebastian; Vargas-Muñoz, Leidy Johana; Saldarriaga-Córdoba, Mónica; Cifuentes, Yeimy; Perafan, Carlos

2017-04-01

Theraphosidae spider venoms are well known for possess a complex mixture of protein and non-protein compounds in their venom. The objective of this study was to report and identify different proteins translated from the venom gland DNA information of the recently described Theraphosidae spider Pamphobeteus verdolaga. Using a venom gland transcriptomic analysis, we reported a set of the first complete sequences of seven different proteins of the recenlty described Theraphosidae spider P. verdolaga. Protein analysis indicates the presence of different proteins on the venom composition of this new spider, some of them uncommon in the Theraphosidae family. MS/MS analysis of P. verdolaga showed different fragments matching sphingomyelinases (sicaritoxin), barytoxins, hexatoxins, latroinsectotoxins, and linear (zadotoxins) peptides. Only four of the MS/MS fragments showed 100% sequence similarity with one of the transcribed proteins. Transcriptomic analysis showed the presence of different groups of proteins like phospholipases, hyaluronidases, inhibitory cysteine knots (ICK) peptides among others. The three database of protein domains used in this study (Pfam, SMART and CDD) showed congruency in the search of unique conserved protein domain for only four of the translated proteins. Those proteins matched with EF-hand proteins, cysteine rich secretory proteins, jingzhaotoxins, theraphotoxins and hexatoxins, from different Mygalomorphae spiders belonging to the families Theraphosidae, Barychelidae and Hexathelidae. None of the analyzed sequences showed a complete 100% similarity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Small Scaffolds, Big Potential: Developing Miniature Proteins as Therapeutic Agents.

PubMed

Holub, Justin M

2017-09-01

Preclinical Research Miniature proteins are a class of oligopeptide characterized by their short sequence lengths and ability to adopt well-folded, three-dimensional structures. Because of their biomimetic nature and synthetic tractability, miniature proteins have been used to study a range of biochemical processes including fast protein folding, signal transduction, catalysis and molecular transport. Recently, miniature proteins have been gaining traction as potential therapeutic agents because their small size and ability to fold into defined tertiary structures facilitates their development as protein-based drugs. This research overview discusses emerging developments involving the use of miniature proteins as scaffolds to design novel therapeutics for the treatment and study of human disease. Specifically, this review will explore strategies to: (i) stabilize miniature protein tertiary structure; (ii) optimize biomolecular recognition by grafting functional epitopes onto miniature protein scaffolds; and (iii) enhance cytosolic delivery of miniature proteins through the use of cationic motifs that facilitate endosomal escape. These objectives are discussed not only to address challenges in developing effective miniature protein-based drugs, but also to highlight the tremendous potential miniature proteins hold for combating and understanding human disease. Drug Dev Res 78 : 268-282, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer.

PubMed

Bhuripanyo, Karan; Wang, Yiyang; Liu, Xianpeng; Zhou, Li; Liu, Ruochuan; Duong, Duc; Zhao, Bo; Bi, Yingtao; Zhou, Han; Chen, Geng; Seyfried, Nicholas T; Chazin, Walter J; Kiyokawa, Hiroaki; Yin, Jun

2018-01-01

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct "orthogonal UB transfer (OUT)" cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N -methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and β-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress.

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer

PubMed Central

Bhuripanyo, Karan; Wang, Yiyang; Liu, Xianpeng; Zhou, Li; Liu, Ruochuan; Duong, Duc; Zhao, Bo; Bi, Yingtao; Zhou, Han; Chen, Geng; Seyfried, Nicholas T.; Chazin, Walter J.; Kiyokawa, Hiroaki; Yin, Jun

2018-01-01

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct “orthogonal UB transfer (OUT)” cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N-methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and β-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress. PMID:29326975

Robust global identifiability theory using potentials--Application to compartmental models.

PubMed

Wongvanich, N; Hann, C E; Sirisena, H R

2015-04-01

This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploiting three kinds of interface propensities to identify protein binding sites.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2009-08-01

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. In this study, we present a building block of proteins called order profiles to use the evolutionary information of the protein sequence frequency profiles and apply this building block to produce a class of propensities called order profile interface propensities. For comparisons, we revisit the usage of residue interface propensities and binary profile interface propensities for protein binding site prediction. Each kind of propensities combined with sequence profiles and accessible surface areas are inputted into SVM. When tested on four types of complexes (hetero-permanent complexes, hetero-transient complexes, homo-permanent complexes and homo-transient complexes), experimental results show that the order profile interface propensities are better than residue interface propensities and binary profile interface propensities. Therefore, order profile is a suitable profile-level building block of the protein sequences and can be widely used in many tasks of computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the protein remote homology detection.

Web-Based Computational Chemistry Education with CHARMMing III: Reduction Potentials of Electron Transfer Proteins

PubMed Central

Perrin, B. Scott; Miller, Benjamin T.; Schalk, Vinushka; Woodcock, H. Lee; Brooks, Bernard R.; Ichiye, Toshiko

2014-01-01

A module for fast determination of reduction potentials, E°, of redox-active proteins has been implemented in the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org). The free energy of reduction, which is proportional to E°, is composed of an intrinsic contribution due to the redox site and an environmental contribution due to the protein and solvent. Here, the intrinsic contribution is selected from a library of pre-calculated density functional theory values for each type of redox site and redox couple, while the environmental contribution is calculated from a crystal structure of the protein using Poisson-Boltzmann continuum electrostatics. An accompanying lesson demonstrates a calculation of E°. In this lesson, an ionizable residue in a [4Fe-4S]-protein that causes a pH-dependent E° is identified, and the E° of a mutant that would test the identification is predicted. This demonstration is valuable to both computational chemistry students and researchers interested in predicting sequence determinants of E° for mutagenesis. PMID:25058418

The potential of protein-nanomaterial interaction for advanced drug delivery.

PubMed

Peng, Qiang; Mu, Huiling

2016-03-10

Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself, would be the real substance the organs and cells firstly encounter. Consequently, the behavior of nanomaterials in vivo is uncontrollable and some undesired effects may occur, like rapid clearance from blood stream; risk of capillary blockage; loss of targeting capacity; and potential toxicity. Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized by selected protein corona using endogenous proteins would have greater promise for clinical use. In this review, we aim to provide a comprehensive understanding of protein-nanomaterial interaction. Importantly, a discussion about how to use such interaction is launched and some possible applications of such interaction for advanced drug delivery are presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

PubMed

Zhang, Changsheng; Tang, Bo; Wang, Qian; Lai, Luhua

2014-10-01

Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we used a protein-protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all-to-all protein-protein docking run on a large dataset was performed. The three-dimensional rigid docking program SDOCK was used to examine protein-protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z-score, and convergency of the low-score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all-to-all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor-α (TNFα), which is a well-known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top-ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein-protein docking for the discovery of novel binding proteins for specific protein targets. © 2014 Wiley Periodicals, Inc.

High-protein goat's milk diet identified through newborn screening: clinical warning of a potentially dangerous dietetic practice.

PubMed

Maines, Evelina; Gugelmo, Giorgia; Tadiotto, Elisa; Pietrobelli, Angelo; Campostrini, Natascia; Pasini, Andrea; Ion-Popa, Florina; Vincenzi, Monica; Teofoli, Francesca; Camilot, Marta; Bordugo, Andrea

2017-10-01

Breast-feeding is an unequalled way of providing optimal food for infants' healthy growth and development and the WHO recommends that infants should be exclusively breast-fed for the first 6 months of life. For mothers who are unable to breast-feed or who decide not to, infant formulas are the safest alternative. Despite recommendations, it is possible that parents make potentially harmful nutritional choices for their children because of cultural beliefs or misinformation on infant nutrition. We describe a possible health risk of not breast-feeding, highlighting a potentially dangerous dietetic practice. Design/Setting/Subjects We report the case of a newborn who was fed with undiluted goat's milk because her mother could not breast-feed and was not aware of infant formulas. The dietary mistake was detected because of a positive expanded newborn screening result, characterized by severe hypertyrosinaemia with high methionine and phenylalanine levels, a pattern suggestive of severe liver impairment. The pattern of plasma amino acids was related to a goat's milk diet, because of its very different composition compared with human milk and infant formula. Our experience demonstrates that, when breast-feeding is not possible or is not exclusive, infants may be at risk of dangerous nutritional practices, including diets with very high protein content, such as a goat's milk diet. Families of not breast-fed infants may need appropriate advice on safe alternatives for infant nutrition to avoid the risks of inappropriate diets.

PUF Proteins: Cellular Functions and Potential Applications.

PubMed

Kiani, Seyed Jalal; Taheri, Tahereh; Rafati, Sima; Samimi-Rad, Katayoun

2017-01-01

RNA-binding proteins play critical roles in the regulation of gene expression. Among several families of RNA-binding proteins, PUF (Pumilio and FBF) proteins have been the subject of extensive investigations, as they can bind RNA in a sequence-specific manner and they are evolutionarily conserved among a wide range of organisms. The outstanding feature of these proteins is a highly conserved RNA-binding domain, which is known as the Pumilio-homology domain (PUM-HD) that mostly consists of eight tandem repeats. Each repeat recognizes an RNA base with a simple three-letter code that can be programmed in order to change the sequence-specificity of the protein. Using this tailored architecture, researchers have been able to change the specificity of the PUM-HD and target desired transcripts in the cell, even in subcellular compartments. The potential applications of this versatile tool in molecular cell biology seem unbounded and the use of these factors in pharmaceutics might be an interesting field of study in near future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling

PubMed Central

MacDonald, James T.; Kelley, Lawrence A.; Freemont, Paul S.

2013-01-01

Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from http

A systematic analysis of the PARP protein family identifies new functions critical for cell physiology

PubMed Central

Vyas, Sejal; Chesarone-Cataldo, Melissa; Todorova, Tanya; Huang, Yun-Han; Chang, Paul

2013-01-01

The poly(ADP-ribose) polymerase (PARP) family of proteins use NAD+ as their substrate to modify acceptor proteins with adenosine diphosphate-ribose (ADPr) modifications. The function of most PARPs under physiological conditions is unknown. Here, to better understand this protein family, we systematically analyze the cell cycle localization of each PARP and of poly(ADP-ribose), a product of PARP activity, then identify the knock-down phenotype of each protein and perform secondary assays to elucidate function. We show that most PARPs are cytoplasmic, identify cell cycle differences in the ratio of nuclear to cytoplasmic poly(ADP-ribose), and identify four phenotypic classes of PARP function. These include the regulation of membrane structures, cell viability, cell division, and the actin cytoskeleton. Further analysis of PARP14 shows that it is a component of focal adhesion complexes required for proper cell motility and focal adhesion function. In total, we show that PARP proteins are critical regulators of eukaryotic physiology. PMID:23917125

Identifying potential academic leaders

PubMed Central

White, David; Krueger, Paul; Meaney, Christopher; Antao, Viola; Kim, Florence; Kwong, Jeffrey C.

2016-01-01

Objective To identify variables associated with willingness to undertake leadership roles among academic family medicine faculty. Design Web-based survey. Bivariate and multivariable analyses (logistic regression) were used to identify variables associated with willingness to undertake leadership roles. Setting Department of Family and Community Medicine at the University of Toronto in Ontario. Participants A total of 687 faculty members. Main outcome measures Variables related to respondents’ willingness to take on various academic leadership roles. Results Of all 1029 faculty members invited to participate in the survey, 687 (66.8%) members responded. Of the respondents, 596 (86.8%) indicated their level of willingness to take on various academic leadership roles. Multivariable analysis revealed that the predictors associated with willingness to take on leadership roles were as follows: pursuit of professional development opportunities (odds ratio [OR] 3.79, 95% CI 2.29 to 6.27); currently holding at least 1 leadership role (OR 5.37, 95% CI 3.38 to 8.53); a history of leadership training (OR 1.86, 95% CI 1.25 to 2.78); the perception that mentorship is important for one’s current role (OR 2.25, 95% CI 1.40 to 3.60); and younger age (OR 0.97, 95% CI 0.95 to 0.99). Conclusion Willingness to undertake new or additional leadership roles was associated with 2 variables related to leadership experiences, 2 variables related to perceptions of mentorship and professional development, and 1 demographic variable (younger age). Interventions that support opportunities in these areas might expand the pool and strengthen the academic leadership potential of faculty members. PMID:27331226

Recombinant expression of in silico identified Bcell epitope of epsilon toxin of Clostridium perfringens in translational fusion with a carrier protein.

PubMed

Kaushik, Himani; Deshmukh, Sachin; Mathur, Deepika Dayal; Tiwari, Archana; Garg, Lalit C

2013-01-01

Epsilon toxin secreted by Clostridium perfringens types B and D has been directly implicated as the causative agent of fatal enterotoxemia in domestic animals. The aim of the present study is to use in silico approach for identification of B-cell epitope(s) of epsilon toxin, and its expression in fusion with a carrier protein to analyze its potential as vaccine candidate(s). Using different computational analyses and bioinformatics tools, a number of antigenic determinant regions of epsilon toxin were identified. One of the B cell epitopes of epsilon toxin comprising the region (amino acids 40-62) was identified as a promising antigenic determinant. This Etx epitope (Etx40-62) was cloned and expressed as a translational fusion with B-subunit of heat labile enterotoxin (LTB) of E. coli in a secretory expression system. Similar to the native LTB, the recombinant fusion protein retained the ability to pentamerize and bind to GM1 ganglioside receptor of LTB. The rLTB.Etx40-62 could be detected both with anti-Etx and anti-LTB antisera. The rLTB.Etx40-62 fusion protein thus can be evaluated as a potential vaccine candidate against C. perfringens. aa - amino acid(s), Etx - epsilon toxin of Clostridium perfringens, LTB - B-subunit of heat labile enterotoxin of E. coli.

LigSearch: a knowledge-based web server to identify likely ligands for a protein target

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, Tjaart A. P. de; Laskowski, Roman A.; Duban, Mark-Eugene

LigSearch is a web server for identifying ligands likely to bind to a given protein. Identifying which ligands might bind to a protein before crystallization trials could provide a significant saving in time and resources. LigSearch, a web server aimed at predicting ligands that might bind to and stabilize a given protein, has been developed. Using a protein sequence and/or structure, the system searches against a variety of databases, combining available knowledge, and provides a clustered and ranked output of possible ligands. LigSearch can be accessed at http://www.ebi.ac.uk/thornton-srv/databases/LigSearch.

Peroxiredoxin I protein, a potential biomarker of hydronephrosis in fetal mice exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

PubMed

Liu, Mingxue; Liu, Jing; Liu, Xing; Wei, Guanghui

2014-06-01

In previous studies, we established an animal model of human congenital hydronephrosis with exposure of developing mice to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), but the etiopathogenesis is not entirely clear. The present study was to identify the changes that may be involved in the etiology at the protein level. C57BL/6J mice fetuses were treated with TCDD. Comparative proteomic analysis was adopted to identify the proteins associated with hydronephrosis induced by TCDD. Two-dimensional electrophoresis display revealed that 19 protein spots were differentially expressed in the upper urinary tract tissues in fetal mice after exposure to TCDD. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) identified 12 up-regulated proteins: peroxiredoxin I (Prx I), cadherin 6, gamma-actin, radixin, desmin, type II transforming growth factor-beta receptor, chromogranin B, serum albumin precursor, transferrin, hypothetical protein LOC70984, lipk protein, and zinc finger protein 336. Histochemical staining indicated that Prx I protein was positively expressed in the ureteric epithelium in the treated group, and not in the control group, which is consistent with MALDI-TOF-MS. Prx I protein may be a potential biomarker or responsive protein of hydronephrosis in fetal mice induced by TCDD. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion*

PubMed Central

Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas

2016-01-01

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394

Potential toxicity of graphene to cell functions via disrupting protein-protein interactions.

PubMed

Luan, Binquan; Huynh, Tien; Zhao, Lin; Zhou, Ruhong

2015-01-27

While carbon-based nanomaterials such as graphene and carbon nanotubes (CNTs) have become popular in state-of-the-art nanotechnology, their biological safety and underlying molecular mechanism is still largely unknown. Experimental studies have been focused at the cellular level and revealed good correlations between cell's death and the application of CNTs or graphene. Using large-scale all-atom molecular dynamics simulations, we theoretically investigate the potential toxicity of graphene to a biological cell at molecular level. Simulation results show that the hydrophobic protein-protein interaction (or recognition) that is essential to biological functions can be interrupted by a graphene nanosheet. Due to the hydrophobic nature of graphene, it is energetically favorable for a graphene nanosheet to enter the hydrophobic interface of two contacting proteins, such as a dimer. The forced separation of two functional proteins can disrupt the cell's metabolism and even lead to the cell's mortality.

Assessment of potential adjuvanticity of Cry proteins.

PubMed

Joshi, Saurabh S; Barnett, Brian; Doerrer, Nancy G; Glenn, Kevin; Herman, Rod A; Herouet-Guicheney, Corinne; Hunst, Penny; Kough, John; Ladics, Gregory S; McClain, Scott; Papineni, Sabitha; Poulsen, Lars K; Rascle, Jean-Baptiste; Tao, Ai-Lin; van Ree, Ronald; Ward, Jason; Bowman, Christal C

2016-08-01

Genetically modified (GM) crops have achieved success in the marketplace and their benefits extend beyond the overall increase in harvest yields to include lowered use of insecticides and decreased carbon dioxide emissions. The most widely grown GM crops contain gene/s for targeted insect protection, herbicide tolerance, or both. Plant expression of Bacillus thuringiensis (Bt) crystal (Cry) insecticidal proteins have been the primary way to impart insect resistance in GM crops. Although deemed safe by regulatory agencies globally, previous studies have been the basis for discussions around the potential immuno-adjuvant effects of Cry proteins. These studies had limitations in study design. The studies used animal models with extremely high doses of Cry proteins, which when given using the ig route were co-administered with an adjuvant. Although the presumption exists that Cry proteins may have immunostimulatory activity and therefore an adjuvanticity risk, the evidence shows that Cry proteins are expressed at very low levels in GM crops and are unlikely to function as adjuvants. This conclusion is based on critical review of the published literature on the effects of immunomodulation by Cry proteins, the history of safe use of Cry proteins in foods, safety of the Bt donor organisms, and pre-market weight-of-evidence-based safety assessments for GM crops. Copyright © 2016 Elsevier Inc. All rights reserved.

A new computational strategy for identifying essential proteins based on network topological properties and biological information.

PubMed

Qin, Chao; Sun, Yongqi; Dong, Yadong

2017-01-01

Essential proteins are the proteins that are indispensable to the survival and development of an organism. Deleting a single essential protein will cause lethality or infertility. Identifying and analysing essential proteins are key to understanding the molecular mechanisms of living cells. There are two types of methods for predicting essential proteins: experimental methods, which require considerable time and resources, and computational methods, which overcome the shortcomings of experimental methods. However, the prediction accuracy of computational methods for essential proteins requires further improvement. In this paper, we propose a new computational strategy named CoTB for identifying essential proteins based on a combination of topological properties, subcellular localization information and orthologous protein information. First, we introduce several topological properties of the protein-protein interaction (PPI) network. Second, we propose new methods for measuring orthologous information and subcellular localization and a new computational strategy that uses a random forest prediction model to obtain a probability score for the proteins being essential. Finally, we conduct experiments on four different Saccharomyces cerevisiae datasets. The experimental results demonstrate that our strategy for identifying essential proteins outperforms traditional computational methods and the most recently developed method, SON. In particular, our strategy improves the prediction accuracy to 89, 78, 79, and 85 percent on the YDIP, YMIPS, YMBD and YHQ datasets at the top 100 level, respectively.

Differential proteomic analysis to identify proteins associated with quality traits of frozen mud shrimp (Solenocera melantho) using an iTRAQ-based strategy.

PubMed

Shi, Jing; Zhang, Longteng; Lei, Yutian; Shen, Huixing; Yu, Xunpei; Luo, Yongkang

2018-06-15

An iTRAQ-based strategy was applied to investigate proteome changes in mud shrimp during long-term frozen storage under different conditions. A total of 226 proteins was identified as differential abundance proteins (DAPs) in mud shrimp from two frozen treatment groups (-20 °C and -40 °C) compared with the fresh control group. The proteome changes in mud shrimp muscle stored under -20 °C was much greater than that under -40 °C. Correlation analysis between DAPs and quality traits of mud shrimp muscle showed that 12 proteins were correlated closely with color (L ∗ , a ∗ , and b ∗ value) and texture (hardness, elasticity, and chewiness). Bioinformatic analysis revealed that most of these proteins were involved in protein structure, metabolic enzymes, and protein turnover. Among them, several proteins might be potential protein markers for color, and some proteins are good candidate predictors for textural properties of mud shrimp muscle. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lsa63, a newly identified surface protein of Leptospira interrogans binds laminin and collagen IV.

PubMed

Vieira, Monica L; de Morais, Zenaide M; Gonçales, Amane P; Romero, Eliete C; Vasconcellos, Silvio A; Nascimento, Ana L T O

2010-01-01

Leptospira interrogans is the etiological agent of leptospirosis, a zoonotic disease that affects populations worldwide. We have identified in proteomic studies a protein that is encoded by the gene LIC10314 and expressed in virulent strain of L. interrogans serovar Pomona. This protein was predicted to be surface exposed by PSORT program and contains a p83/100 domain identified by BLAST analysis that is conserved in protein antigens of several strains of Borrelia and Treponema spp. The proteins containing this domain have been claimed antigen candidates for serodiagnosis of Lyme borreliosis. Thus, we have cloned the LIC10314 and expressed the protein in Escherichia coli BL21-SI strain by using the expression vector pAE. The recombinant protein tagged with N-terminal hexahistidine was purified by metal-charged chromatography and characterized by circular dichroism spectroscopy. This protein is conserved among several species of pathogenic Leptospira and absent in the saprophytic strain L. biflexa. We confirm by liquid-phase immunofluorescence assays with living organisms that this protein is most likely a new surface leptospiral protein. The ability of the protein to mediate attachment to ECM components was evaluated by binding assays. The leptospiral protein encoded by LIC10314, named Lsa63 (Leptospiral surface adhesin of 63kDa), binds strongly to laminin and collagen IV in a dose-dependent and saturable fashion. In addition, Lsa63 is probably expressed during infection since it was recognized by antibodies of serum samples of confirmed-leptospirosis patients in convalescent phase of the disease. Altogether, the data suggests that this novel identified surface protein may be involved in leptospiral pathogenesis. 2009 The British Infection Society. Published by Elsevier Ltd. All rights reserved.

Three newly identified galectin homologues from triangle sail mussel (Hyriopsis cumingii) function as potential pattern-recognition receptors.

PubMed

Zhao, Ling-Ling; Hui, Kaimin; Wang, Yu-Qing; Wang, Yue; Ren, Qian; Li, Xin-Cang

2018-05-01

Galactoside-binding lectins, also known as galectins, play crucial roles in innate immune response in invertebrates. In this study, three cDNA sequences from Hyriopsis cumingii were identified and collectively called HcGalec genes. Each of the three deduced HcGalec proteins contained a galactose-binding lectin domain or a GLECT domain. All the three HcGalec genes are mainly present in the hepatopancreas and gills, and their expression is induced at 24 h after bacterial challenge. Three recombinant HcGalec proteins can bind and agglutinate (Ca 2+ -dependent) various microorganisms, including Gram-positive and Gram-negative bacteria. These proteins can attach to mannan and peptidoglycan. Meanwhile, the expression of the three HcGalec genes in the gills were significantly down-regulated after dsRNA interference (HcGalec1-RNAi, HcGalec2-RNAi, and HcGalec3-RNAi) and Vibrio parahaemolyticus injection. The expression levels of some antimicrobial peptides, including lysozyme 1 and lysozyme 2, were also markedly decreased after dsRNA interference. Overall, these results suggested that these three HcGalec proteins may function as potential receptors participating in the innate immune responses of H. cumingii against bacterial infection. Copyright © 2018 Elsevier Ltd. All rights reserved.

In-situ Click Reaction Coupled with Quantitative Proteomics for Identifying Protein Targets of Catechol Estrogens.

PubMed

Liang, Huei-Chen; Liu, Yi-Chen; Chen, Hsin; Ku, Ming Chun; Do, Quynh-Trang; Wang, Chih-Yen; Tzeng, Shun-Fen; Chen, Shu-Hui

2018-06-13

Catechol estrogens (CEs) are metabolic electrophiles that actively undergo covalent interaction with cellular proteins, influencing molecular function. There is no feasible method to identify their binders in a living system. Herein, we developed a click chemistry-based approach using ethinylestradiol (EE2) as the precursor probe coupled with quantitative proteomics to identify protein targets of CEs and classify their binding strengths. Using in-situ metabolic conversion and click reaction in liver microsomes, CEs-protein complex was captured by the probe, digested by trypsin, stable isotope labeled via reductive amination, and analyzed by liquid chromatography-mass spectrometry (LC-MS). A total of 334 liver proteins were repeatedly identified (n  2); 274 identified proteins were classified as strong binders based on precursor mass mapping. The binding strength was further scaled by D/H ratio (activity probe/solvent): 259 strong binders had D/H > 5.25; 46 weak binders had 5.25 > D/H > 1; 5 non-specific binders (keratins) had D/H < 1. These results were confirmed using spiked covalent control (strong binder) and noncovalent control (weak binder), as well as in vitro testing of cytochrome c (D/H = 5.9) which showed covalent conjugation with CEs. Many identified strong binders, such as glutathione transferase, catechol-O-methyl transferase, superoxide dismutase, catalase, glutathione peroxidase, and cytochrome c, are involved in cellular redox processes or detoxification activities. CE conjugation was shown to suppress the superoxide oxidase activity of cytochrome c, suggesting that CEs modification may alter the redox action of cellular proteins. Due to structural similarity and inert alkyne group, EE2 probe is very likely to capture protein targets of CEs in general. Thus, this strategy can be adopted to explore the biological impact of CEs modification in living systems.

CoMoDo: identifying dynamic protein domains based on covariances of motion.

PubMed

Wieninger, Silke A; Ullmann, G Matthias

2015-06-09

Most large proteins are built of several domains, compact units which enable functional protein motions. Different domain assignment approaches exist, which mostly rely on concepts of stability, folding, and evolution. We describe the automatic assignment method CoMoDo, which identifies domains based on protein dynamics. Covariances of atomic fluctuations, here calculated by an Elastic Network Model, are used to group residues into domains of different hierarchical levels. The so-called dynamic domains facilitate the study of functional protein motions involved in biological processes like ligand binding and signal transduction. By applying CoMoDo to a large number of proteins, we demonstrate that dynamic domains exhibit features absent in the commonly assigned structural domains, which can deliver insight into the interactions between domains and between subunits of multimeric proteins. CoMoDo is distributed as free open source software at www.bisb.uni-bayreuth.de/CoMoDo.html .

Probabilistic analysis for identifying the driving force of protein folding

NASA Astrophysics Data System (ADS)

Tokunaga, Yoshihiko; Yamamori, Yu; Matubayasi, Nobuyuki

2018-03-01

Toward identifying the driving force of protein folding, energetics was analyzed in water for Trp-cage (20 residues), protein G (56 residues), and ubiquitin (76 residues) at their native (folded) and heat-denatured (unfolded) states. All-atom molecular dynamics simulation was conducted, and the hydration effect was quantified by the solvation free energy. The free-energy calculation was done by employing the solution theory in the energy representation, and it was seen that the sum of the protein intramolecular (structural) energy and the solvation free energy is more favorable for a folded structure than for an unfolded one generated by heat. Probabilistic arguments were then developed to determine which of the electrostatic, van der Waals, and excluded-volume components of the interactions in the protein-water system governs the relative stabilities between the folded and unfolded structures. It was found that the electrostatic interaction does not correspond to the preference order of the two structures. The van der Waals and excluded-volume components were shown, on the other hand, to provide the right order of preference at probabilities of almost unity, and it is argued that a useful modeling of protein folding is possible on the basis of the excluded-volume effect.

Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

PubMed

Zheng, Wu; Blake, Catherine

2015-10-01

Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

A novel assay to identify the trafficking proteins that bind to specific vesicle populations

PubMed Central

Bentley, Marvin; Banker, Gary

2016-01-01

Here we describe a method capable of identifying interactions between candidate trafficking proteins and a defined vesicle population in intact cells. The assay involves the expression of an FKBP12-rapamycin–binding domain (FRB)–tagged candidate vesicle-binding protein that can be inducibly linked to an FKBP-tagged molecular motor. If the FRB-tagged candidate protein binds the labeled vesicles, then linking the FRB and FKBP domains recruits motors to the vesicles and causes a predictable, highly distinctive change in vesicle trafficking. We describe two versions of the assay: a general protocol for use in cells with a typical microtubule-organizing center and a specialized protocol designed to detect protein-vesicle interactions in cultured neurons. We have successfully used this assay to identify kinesins and Rabs that bind to a variety of different vesicle populations. In principle, this assay could be used to investigate interactions between any category of vesicle trafficking proteins and any vesicle population that can be specifically labeled. PMID:26621371

PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

PubMed

Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

2016-09-01

Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e

Phage-display for identifying peptides that bind the spike protein of transmissible gastroenteritis virus and possess diagnostic potential

USDA-ARS?s Scientific Manuscript database

The spike (S) protein is a key structural protein of coronaviruses including, the porcine transmissible gastroenteritis virus (TGEV). The S protein is a type I membrane glycoprotein located in the viral envelope and is responsible for mediating the binding of viral particles to specific cell recepto...

Genome wide approaches to identify protein-DNA interactions.

PubMed

Ma, Tao; Ye, Zhenqing; Wang, Liguo

2018-05-29

Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome-wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Proteomic analysis identifies differentially expressed proteins after red propolis treatment in Hep-2 cells.

PubMed

Frozza, Caroline Olivieri da Silva; Ribeiro, Tanara da Silva; Gambato, Gabriela; Menti, Caroline; Moura, Sidnei; Pinto, Paulo Marcos; Staats, Charley Christian; Padilha, Francine Ferreira; Begnini, Karine Rech; de Leon, Priscila Marques Moura; Borsuk, Sibele; Savegnago, Lucielli; Dellagostin, Odir; Collares, Tiago; Seixas, Fabiana Kömmling; Henriques, João Antonio Pêgas; Roesch-Ely, Mariana

2014-01-01

Here we investigated alterations in the protein profile of Hep-2 treated with red propolis using two-dimensional electrophoresis associated to mass spectrometry and apoptotic rates of cells treated with and without red propolis extracts through TUNEL and Annexin-V assays. A total of 325 spots were manually excised from the two-dimensional gel electrophoresis and 177 proteins were identified using LC-MS-MS. Among all proteins identified that presented differential expression, most were down-regulated in presence of red propolis extract at a concentration of 120 μg/mL (IC50): GRP78, PRDX2, LDHB, VIM and TUBA1A. Only two up-regulated proteins were identified in this study in the non-cytotoxic (6 μg/mL) red propolis treated group: RPLP0 and RAD23B. TUNEL staining assay showed a markedly increase in the mid- to late-stage apoptosis of Hep-2 cells induced by red propolis at concentrations of 60 and 120 μg/mL when compared with non-treated cells. The increase of late apoptosis was confirmed by in situ Annexin-V analysis in which red propolis extract induced late apoptosis in a dose-dependent manner. The differences in tumor cell protein profiles warrant further investigations including isolation of major bioactive compounds of red propolis in different cell lines using proteomics and molecular tests to validate the protein expression here observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Library of Plasmodium vivax Recombinant Merozoite Proteins Reveals New Vaccine Candidates and Protein-Protein Interactions

PubMed Central

Hostetler, Jessica B.; Sharma, Sumana; Bartholdson, S. Josefin; Wright, Gavin J.; Fairhurst, Rick M.; Rayner, Julian C.

2015-01-01

Background A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP) and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC), and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion. Methodology/Principal Findings We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further

In Silico Screening of the Human Gut Metaproteome Identifies Th17-Promoting Peptides Encrypted in Proteins of Commensal Bacteria

PubMed Central

Hidalgo-Cantabrana, Claudio; Moro-García, Marco A.; Blanco-Míguez, Aitor; Fdez-Riverola, Florentino; Lourenço, Anália; Alonso-Arias, Rebeca; Sánchez, Borja

2017-01-01

Scientific studies focused on the role of the human microbiome over human health have generated billions of gigabits of genetic information during the last decade. Nowadays integration of all this information in public databases and development of pipelines allowing us to biotechnologically exploit this information are urgently needed. Prediction of the potential bioactivity of the products encoded by the human gut microbiome, or metaproteome, is the first step for identifying proteins responsible for the molecular interaction between microorganisms and the immune system. We have recently published the Mechanism of Action of the Human Microbiome (MAHMI) database (http://www.mahmi.org), conceived as a resource compiling peptide sequences with a potential immunomodulatory activity. Fifteen out of the 300 hundred million peptides contained in the MAHMI database were synthesized. These peptides were identified as being encrypted in proteins produced by gut microbiota members, they do not contain cleavage points for the major intestinal endoproteases and displayed high probability to have immunomodulatory bioactivity. The bacterial peptides FR-16 and LR-17 encrypted in proteins from Bifidobacterium longum DJ010A and Bifidobacterium fragilis YCH46 respectively, showed the higher immune modulation capability over human peripheral blood mononuclear cells. Both peptides modulated the immune response toward increases in the Th17 and decreases in the Th1 cell response, together with an induction of IL-22 production. These results strongly suggest the combined use of bioinformatics and in vitro tools as a first stage in the screening of bioactive peptides encrypted in the human gut metaproteome. PMID:28943872

Comparative gene expression profiling of in vitro differentiated megakaryocytes and erythroblasts identifies novel activatory and inhibitory platelet membrane proteins.

PubMed

Macaulay, Iain C; Tijssen, Marloes R; Thijssen-Timmer, Daphne C; Gusnanto, Arief; Steward, Michael; Burns, Philippa; Langford, Cordelia F; Ellis, Peter D; Dudbridge, Frank; Zwaginga, Jaap-Jan; Watkins, Nicholas A; van der Schoot, C Ellen; Ouwehand, Willem H

2007-04-15

To identify previously unknown platelet receptors we compared the transcriptomes of in vitro differentiated megakaryocytes (MKs) and erythroblasts (EBs). RNA was obtained from purified, biologically paired MK and EB cultures and compared using cDNA microarrays. Bioinformatical analysis of MK-up-regulated genes identified 151 transcripts encoding transmembrane domain-containing proteins. Although many of these were known platelet genes, a number of previously unidentified or poorly characterized transcripts were also detected. Many of these transcripts, including G6b, G6f, LRRC32, LAT2, and the G protein-coupled receptor SUCNR1, encode proteins with structural features or functions that suggest they may be involved in the modulation of platelet function. Immunoblotting on platelets confirmed the presence of the encoded proteins, and flow cytometric analysis confirmed the expression of G6b, G6f, and LRRC32 on the surface of platelets. Through comparative analysis of expression in platelets and other blood cells we demonstrated that G6b, G6f, and LRRC32 are restricted to the platelet lineage, whereas LAT2 and SUCNR1 were also detected in other blood cells. The identification of the succinate receptor SUCNR1 in platelets is of particular interest, because physiologically relevant concentrations of succinate were shown to potentiate the effect of low doses of a variety of platelet agonists.

Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

PubMed

Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

2017-05-01

The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fukunaga, Satoki; Environmental Health Science Laboratory, Sumitomo Chemical Co., Ltd., 3-1-98 Kasugade-Naka, Konohana-ku, Osaka 554-8558; Kakehashi, Anna

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective ofmore » initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.« less

Identifying Potential Kidney Donors Using Social Networking Websites

PubMed Central

Chang, Alexander; Anderson, Emily E.; Turner, Hang T.; Shoham, David; Hou, Susan H.; Grams, Morgan

2013-01-01

Social networking sites like Facebook may be a powerful tool for increasing rates of live kidney donation. They allow for wide dissemination of information and discussion, and could lessen anxiety associated with a face-to-face request for donation. However, sparse data exist on the use of social media for this purpose. We searched Facebook, the most popular social networking site, for publicly available English-language pages seeking kidney donors for a specific individual, abstracting information on the potential recipient, characteristics of the page itself, and whether potential donors were tested. In the 91 pages meeting inclusion criteria, the mean age of potential recipients was 37 (range: 2–69); 88% were U.S. residents. Other posted information included the individual’s photograph (76%), blood type (64%), cause of kidney disease (43%), and location (71%). Thirty-two percent of pages reported having potential donors tested, and 10% reported receiving a live donor kidney transplant. Those reporting donor testing shared more potential recipient characteristics, provided more information about transplantation, and had higher page traffic. Facebook is already being used to identify potential kidney donors. Future studies should focus on how to safely, ethically, and effectively use social networking sites to inform potential donors and potentially expand live kidney donation. PMID:23600791

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Apel, William A.; Thompson, Vicki S; Lacey, Jeffrey A.; Gentillon, Cynthia A.

2016-08-09

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Identification of discriminant proteins through antibody profiling, methods and apparatus for identifying an individual

DOEpatents

Thompson, Vicki S; Lacey, Jeffrey A; Gentillon, Cynthia A; Apel, William A

2015-03-03

A method for determining a plurality of proteins for discriminating and positively identifying an individual based from a biological sample. The method may include profiling a biological sample from a plurality of individuals against a protein array including a plurality of proteins. The protein array may include proteins attached to a support in a preselected pattern such that locations of the proteins are known. The biological sample may be contacted with the protein array such that a portion of antibodies in the biological sample reacts with and binds to the proteins forming immune complexes. A statistical analysis method, such as discriminant analysis, may be performed to determine discriminating proteins for distinguishing individuals. Proteins of interest may be used to form a protein array. Such a protein array may be used, for example, to compare a forensic sample from an unknown source with a sample from a known source.

Evaluation of Bar, Barnase, and Barstar recombinant proteins expressed in genetically engineered Brassica juncea (Indian mustard) for potential risks of food allergy using bioinformatics and literature searches.

PubMed

Siruguri, Vasanthi; Bharatraj, Dinesh Kumar; Vankudavath, Raju Naik; Mendu, Vishnu Vardhana Rao; Gupta, Vibha; Goodman, Richard E

2015-09-01

The potential allergenicity of Bar, Barnase, and Barstar recombinant proteins expressed in genetically engineered mustard for pollination control in plant breeding was evaluated for regulatory review. To evaluate the potential allergenicity of the Bar, Barnase and Barstar proteins amino acid sequence comparisons were made to those of known and putative allergens, and search for published evidence to the sources of the genes using the AllergenOnline.org database. Initial comparisons in 2012 were performed with version 12 by methods recommended by the Codex Alimentarius Commission and the Indian Council of Medical Research, Government of India. Searches were repeated with version 15 in 2015. A literature search was performed using PubMed to identify reports of allergy associated with the sources of the three transgenes. Potential open reading frames at the DNA insertion site were evaluated for matches to allergens. No significant sequence identity matches were identified with Bar, Barnase or Barstar proteins or potential fusion peptides at the genomic-insert junctions compared to known allergens. No references were identified that associated the sources of the genes with allergy. Based on these results we conclude that the Bar, Barnase and Barstar proteins are unlikely to present any significant risk of food allergy to consumers. Copyright © 2015 Elsevier Ltd. All rights reserved.

The malaria parasite RhopH protein complex interacts with erythrocyte calmyrin identified from a comprehensive erythrocyte protein library.

PubMed

Miura, Toyokazu; Takeo, Satoru; Ntege, Edward H; Otsuki, Hitoshi; Sawasaki, Tatsuya; Ishino, Tomoko; Takashima, Eizo; Tsuboi, Takafumi

2018-06-02

Malaria merozoite apical organelles; microneme and rhoptry secreted proteins play functional roles during and following invasion of host erythrocytes. Among numerous proteins, the rhoptries discharge high molecular weight proteins known as RhopH complex. Recent reports suggest that the RhopH complex is essential for growth and survival of the malaria parasite within erythrocytes. However, an in-depth understanding of the host-parasite molecular interactions is indispensable. Here we utilized a comprehensive mouse erythrocyte protein library consisting of 443 proteins produced by a wheat germ cell-free system, combined with AlphaScreen technology to identify mouse erythrocyte calmyrin as an interacting molecule of the rodent malaria parasite Plasmodium yoelii RhopH complex (PyRhopH). The PyRhopH interaction was dependent on the calmyrin N-terminus and divalent cation capacity. The finding unveils a recommendable and invaluable usefulness of our comprehensive mouse erythrocyte protein library together with the AlphaScreen technology in investigating a wide-range of host-parasite molecular interactions. Copyright © 2018 Elsevier Inc. All rights reserved.

A Novel Proteomics Approach to Identify SUMOylated Proteins and Their Modification Sites in Human Cells*

PubMed Central

Galisson, Frederic; Mahrouche, Louiza; Courcelles, Mathieu; Bonneil, Eric; Meloche, Sylvain; Chelbi-Alix, Mounira K.; Thibault, Pierre

2011-01-01

The small ubiquitin-related modifier (SUMO) is a small group of proteins that are reversibly attached to protein substrates to modify their functions. The large scale identification of protein SUMOylation and their modification sites in mammalian cells represents a significant challenge because of the relatively small number of in vivo substrates and the dynamic nature of this modification. We report here a novel proteomics approach to selectively enrich and identify SUMO conjugates from human cells. We stably expressed different SUMO paralogs in HEK293 cells, each containing a His6 tag and a strategically located tryptic cleavage site at the C terminus to facilitate the recovery and identification of SUMOylated peptides by affinity enrichment and mass spectrometry. Tryptic peptides with short SUMO remnants offer significant advantages in large scale SUMOylome experiments including the generation of paralog-specific fragment ions following CID and ETD activation, and the identification of modified peptides using conventional database search engines such as Mascot. We identified 205 unique protein substrates together with 17 precise SUMOylation sites present in 12 SUMO protein conjugates including three new sites (Lys-380, Lys-400, and Lys-497) on the protein promyelocytic leukemia. Label-free quantitative proteomics analyses on purified nuclear extracts from untreated and arsenic trioxide-treated cells revealed that all identified SUMOylated sites of promyelocytic leukemia were differentially SUMOylated upon stimulation. PMID:21098080

Venom gland transcriptomics for identifying, cataloging, and characterizing venom proteins in snakes.

PubMed

Brahma, Rajeev Kungur; McCleary, Ryan J R; Kini, R Manjunatha; Doley, Robin

2015-01-01

Snake venoms are cocktails of protein toxins that play important roles in capture and digestion of prey. Significant qualitative and quantitative variation in snake venom composition has been observed among and within species. Understanding these variations in protein components is instrumental in interpreting clinical symptoms during human envenomation and in searching for novel venom proteins with potential therapeutic applications. In the last decade, transcriptomic analyses of venom glands have helped in understanding the composition of various snake venoms in great detail. Here we review transcriptomic analysis as a powerful tool for understanding venom profile, variation and evolution. Copyright © 2014 Elsevier Ltd. All rights reserved.

Free energy landscape of protein-like chains with discontinuous potentials

NASA Astrophysics Data System (ADS)

Movahed, Hanif Bayat; van Zon, Ramses; Schofield, Jeremy

2012-06-01

In this article the configurational space of two simple protein models consisting of polymers composed of a periodic sequence of four different kinds of monomers is studied as a function of temperature. In the protein models, hydrogen bond interactions, electrostatic repulsion, and covalent bond vibrations are modeled by discontinuous step, shoulder, and square-well potentials, respectively. The protein-like chains exhibit a secondary alpha helix structure in their folded states at low temperatures, and allow a natural definition of a configuration by considering which beads are bonded. Free energies and entropies of configurations are computed using the parallel tempering method in combination with hybrid Monte Carlo sampling of the canonical ensemble of the discontinuous potential system. The probability of observing the most common configuration is used to analyze the nature of the free energy landscape, and it is found that the model with the least number of possible bonds exhibits a funnel-like free energy landscape at low enough temperature for chains with fewer than 30 beads. For longer proteins, the free landscape consists of several minima, where the configuration with the lowest free energy changes significantly by lowering the temperature and the probability of observing the most common configuration never approaches one due to the degeneracy of the lowest accessible potential energy.

Identifying Potential Protein Targets for Toluene Using a Molecular Similarity Search, in Silico Docking and in Vitro Validation

DTIC Science & Technology

2015-01-01

the Protein Data Bank (http://www.rcsb.org/ pdb /). These structures are the most accurate and can be used for molecular docking. Target flexibility is...crystallized with the different ligands. In total, 240 files with the structures of 37 proteins were downloaded from PDB and used for docking...total, 240 files with protein structures were downloaded from the PDB and used for protein–ligand docking. It is widely accepted that ligand binding

Pathogen effector protein screening in yeast identifies Legionella factors that interfere with membrane trafficking.

PubMed

Shohdy, Nadim; Efe, Jem A; Emr, Scott D; Shuman, Howard A

2005-03-29

Legionella pneumophila invades and replicates intracellularly in human and protozoan hosts. The bacteria use the Icm/Dot type IVB secretion system to translocate effectors that inhibit phagosome maturation and modulate host vesicle trafficking pathways. To understand how L. pneumophila modulates organelle trafficking in host cells, we carried out pathogen effector protein screening in yeast, identifying L. pneumophila genes that produced membrane trafficking [vacuole protein sorting (VPS)] defects in yeast. We identified four L. pneumophila DNA fragments that perturb sorting of vacuolar proteins. Three encode ORFs of unknown function that are translocated via the Icm/Dot transporter from Legionella into macrophages. VPS inhibitor protein (Vip) A is a coiled-coil protein, VipD is a patatin domain-containing protein, and VipF contains an acetyltransferase domain. Processing studies in yeast indicate that VipA, VipD, and VipF inhibit lysosomal protein trafficking by different mechanisms; overexpressing VipA has an effect on carboxypeptidase Y trafficking, whereas VipD interferes with multivesicular body formation at the late endosome and endoplasmic reticulum-to-Golgi body transport. Such differences highlight the multiple strategies L. pneumophila effectors use to subvert host trafficking processes. Using yeast as an effector gene discovery tool allows for a powerful, genetic approach to both the identification of virulence factors and the study of their function.

Release of genetically engineered insects: a framework to identify potential ecological effects

PubMed Central

David, Aaron S; Kaser, Joe M; Morey, Amy C; Roth, Alexander M; Andow, David A

2013-01-01

Genetically engineered (GE) insects have the potential to radically change pest management worldwide. With recent approvals of GE insect releases, there is a need for a synthesized framework to evaluate their potential ecological and evolutionary effects. The effects may occur in two phases: a transitory phase when the focal population changes in density, and a steady state phase when it reaches a new, constant density. We review potential effects of a rapid change in insect density related to population outbreaks, biological control, invasive species, and other GE organisms to identify a comprehensive list of potential ecological and evolutionary effects of GE insect releases. We apply this framework to the Anopheles gambiae mosquito – a malaria vector being engineered to suppress the wild mosquito population – to identify effects that may occur during the transitory and steady state phases after release. Our methodology reveals many potential effects in each phase, perhaps most notably those dealing with immunity in the transitory phase, and with pathogen and vector evolution in the steady state phase. Importantly, this framework identifies knowledge gaps in mosquito ecology. Identifying effects in the transitory and steady state phases allows more rigorous identification of the potential ecological effects of GE insect release. PMID:24198955

Protein Recovery from Secondary Paper Sludge and Its Potential Use as Wood Adhesive

NASA Astrophysics Data System (ADS)

Pervaiz, Muhammad

Secondary sludge is an essential part of biosolids produced through the waste treatment plant of paper mills. Globally paper mills generate around 3.0 million ton of biosolids and in the absence of beneficial applications, the handling and disposal of this residual biomass poses a serious environmental and economic proposition. Secondary paper sludges were investigated in this work for recovery of proteins and their use as wood adhesive. After identifying extracellular polymeric substances as adhesion pre-cursors through analytical techniques, studies were carried out to optimize protein recovery from SS and its comprehensive characterization. A modified physicochemical protocol was developed to recover protein from secondary sludge in substantial quantities. The combined effect of French press and sonication techniques followed by alkali treatment resulted in significant improvement of 44% in the yield of solubilized protein compared to chemical methods. The characterization studies confirmed the presence of common amino acids in recovered sludge protein in significant quantities and heavy metal concentration was reduced after recovery process. The sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis revealed the presence of both low and high molecular weight protein fractions in recovered sludge protein. After establishing the proof-of-concept in the use of recovered sludge protein as wood adhesive, the bonding mechanism of protein adhesives with cellulose substrate was further elucidated in a complementary protein-modification study involving soy protein isolate and its glycinin fractions. The results of this study validated the prevailing bonding theories by proving that surface wetting, protein structure, and type of wood play important role in determining final adhesive strength. Recovered sludge protein was also investigated for its compatibility to formulate hybrid adhesive blends with formaldehyde and bio-based polymers. Apart from chemical

Immunoproteomic identification of immunogenic proteins in Cronobacter sakazakii strain BAA-894.

PubMed

Wang, Jian; Du, Xin-Jun; Lu, Xiao-Nan; Wang, Shuo

2013-03-01

Cronobacter spp. are emerging opportunistic pathogens. Cronobacter sakazakii is considered as the predominant species in all infections. So far, our understanding of the species' immunogens and potential virulence factors of Cronobacter spp. remains limited. In this study, an immunoproteomic approach was used to investigate soluble and insoluble proteins from the genome-sequenced strain C. sakazakii ATCC BAA-894. Proteins were separated using two-dimensional electrophoresis, detected by Western blotting with polyclonal antibodies of C. sakazakii BAA-894, and identified using tandem mass spectrometry (MALDI-MS and MALDI-MS/MS, MS/MSMS). A total of 11 immunoreactive proteins were initially identified in C. sakazakii BAA-894, including two outer membrane proteins, four periplasmic proteins, and five cytoplasmic proteins. In silico functional analysis of the 11 identified proteins indicated three proteins that were initially described as immunogens of pathogenic bacteria. For the remaining eight proteins, one protein was categorized as a potential virulence factor involved in protection against reactive oxygen species, and seven proteins were considered to play potential roles in adhesion, invasion, and biofilm formation. To our knowledge, this is the first time that immunogenic proteins of C. sakazakii BAA-894 have been identified as immunogens and potential virulence factors by an immunoproteomics approach. Future studies should investigate the roles of these proteins in bacterial pathogenesis and modulation of host immune responses during infection to identify their potential as molecular therapeutic targets.

A yeast-based genetic screening to identify human proteins that increase homologous recombination.

PubMed

Collavoli, Anita; Comelli, Laura; Rainaldi, Giuseppe; Galli, Alvaro

2008-05-01

To identify new human proteins implicated in homologous recombination (HR), we set up 'a papillae assay' to screen a human cDNA library using the RS112 strain of Saccharomyces cerevisiae containing an intrachromosomal recombination substrate. We isolated 23 cDNAs, 11 coding for complete proteins and 12 for partially deleted proteins that increased HR when overexpressed in yeast. We characterized the effect induced by the overexpression of the complete human proteasome subunit beta 2, the partially deleted proteasome subunits alpha 3 and beta 8, the ribosomal protein L12, the brain abundant membrane signal protein (BASP1) and the human homologue to v-Ha-RAS (HRAS), which elevated HR by 2-6.5-fold over the control. We found that deletion of the RAD52 gene, which has a key role in most HR events, abolished the increase of HR induced by the proteasome subunits and HRAS; by contrast, the RAD52 deletion did not affect the high level of HR due to BASP1 and RPL12. This suggests that the proteins stimulated yeast HR via different mechanisms. Overexpression of the complete beta 2 human proteasome subunit or the partially deleted alpha 3 and beta 8 subunits increased methyl methanesulphonate (MMS) resistance much more in the rad52 Delta mutant than in the wild-type. Overexpression of RPL12 and BASP1 did not affect MMS resistance in both the wild-type and the rad52 Delta mutant, whereas HRAS decreased MMS resistance in the rad52 Delta mutant. The results indicate that these proteins may interfere with the pathway(s) involved in the repair of MMS-induced DNA damage. Finally, we provide further evidence that yeast is a helpful tool to identify human proteins that may have a regulatory role in HR.

Bioactivities of alternative protein sources and their potential health benefits.

PubMed

Pihlanto, A; Mattila, P; Mäkinen, S; Pajari, A-M

2017-10-18

Increasing the utilisation of plant proteins is needed to support the production of protein-rich foods that could replace animal proteins in the human diet so as to reduce the strain that intensive animal husbandry poses to the environment. Lupins, quinoa and hempseed are significant sources of energy, high quality proteins, fibre, vitamins and minerals. In addition, they contain compounds such as polyphenols and bioactive peptides that can increase the nutritional value of these plants. From the nutritional standpoint, the right combination of plant proteins can supply sufficient amounts of essential amino acids for human requirements. This review aims at providing an overview of the current knowledge of the nutritional properties, beneficial and non-nutritive compounds, storage proteins, and potential health benefits of lupins, quinoa and hempseed.

Proteome analysis of Aspergillus fumigatus identifies glycosylphosphatidylinositol-anchored proteins associated to the cell wall biosynthesis.

PubMed

Bruneau, J M; Magnin, T; Tagat, E; Legrand, R; Bernard, M; Diaquin, M; Fudali, C; Latgé, J P

2001-08-01

Previous studies in Aspergillus fumigatus (Mouyna I., Fontaine T., Vai M., Monod M., Fonzi W. A., Diaquin M., Popolo L., Hartland R. P., Latgé J.-P, J. Biol. Chem. 2000, 275, 14882-14889) have shown that a glucanosyltransferase playing an important role in fungal cell wall biosynthesis is glycosylphosphatidylinositol (GPI) anchored to the membrane. To identify other GPI-anchored proteins putatively involved in cell wall biogenesis, a proteomic analysis has been undertaken in A. fumigatus and the protein data were matched with the yeast genomic data. GPI-anchored proteins of A. fumigatus were released from membrane preparation by an endogenous GPI-phospholipase C, purified by liquid chromatography and separated by two-dimensional electrophoresis. They were characterized by their peptide mass fingerprint through matrix-assisted laser desorption/ionization-time of flight-(MALDI-TOF)-mass spectrometry and by internal amino acid sequencing. Nine GPI-anchored proteins were identified in A. fumigatus. Five of them were homologs of putatively GPI-anchored yeast proteins (Csa1p, Crh1p, Crh2p, Ecm33p, Gas1p) of unknown function but shown by gene disruption analysis to play a role in cell wall morphogenesis. In addition, a comparative study performed with chitin synthase and glucanosyl transferase mutants of A. fumigatus showed that a modification of the growth phenotype seen in these mutants was associated to an alteration of the pattern of GPI-anchored proteins. These results suggest that GPI-anchored proteins identified in this study are involved in A. fumigatus cell wall organization.

Activation tagging in indica rice identifies ribosomal proteins as potential targets for manipulation of water-use efficiency and abiotic stress tolerance in plants.

PubMed

Moin, Mazahar; Bakshi, Achala; Saha, Anusree; Udaya Kumar, M; Reddy, Attipalli R; Rao, K V; Siddiq, E A; Kirti, P B

2016-11-01

We have generated 3900 enhancer-based activation-tagged plants, in addition to 1030 stable Dissociator-enhancer plants in a widely cultivated indica rice variety, BPT-5204. Of them, 3000 were screened for water-use efficiency (WUE) by analysing photosynthetic quantum efficiency and yield-related attributes under water-limiting conditions that identified 200 activation-tagged mutants, which were analysed for flanking sequences at the site of enhancer integration in the genome. We have further selected five plants with low Δ 13 C, high quantum efficiency and increased plant yield compared with wild type for a detailed investigation. Expression studies of 18 genes in these mutants revealed that in four plants one of the three to four tagged genes became activated, while two genes were concurrently up-regulated in the fifth plant. Two genes coding for proteins involved in 60S ribosomal assembly, RPL6 and RPL23A, were among those that became activated by enhancers. Quantitative expression analysis of these two genes also corroborated the results on activating-tagging. The high up-regulation of RPL6 and RPL23A in various stress treatments and the presence of significant cis-regulatory elements in their promoter regions along with the high up-regulation of several of RPL genes in various stress treatments indicate that they are potential targets for manipulating WUE/abiotic stress tolerance. © 2016 John Wiley & Sons Ltd.

The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis.

PubMed

Mao, Yimin; Kuo, Su-Wei; Chen, Le; Heckman, C J; Jiang, M C

2017-01-01

Amyotrophic Lateral Sclerosis (ALS) is a devastative neurodegenerative disease characterized by selective loss of motoneurons. While several breakthroughs have been made in identifying ALS genetic defects, the detailed molecular mechanisms are still unclear. These genetic defects involve in numerous biological processes, which converge to a common destiny: motoneuron degeneration. In addition, the common comorbid Frontotemporal Dementia (FTD) further complicates the investigation of ALS etiology. In this study, we aimed to explore the protein-protein interaction network built on known ALS-causative genes to identify essential proteins and common downstream proteins between classical ALS and ALS+FTD (classical ALS + ALS/FTD) groups. The results suggest that classical ALS and ALS+FTD share similar essential protein set (VCP, FUS, TDP-43 and hnRNPA1) but have distinctive functional enrichment profiles. Thus, disruptions to these essential proteins might cause motoneuron susceptible to cellular stresses and eventually vulnerable to proteinopathies. Moreover, we identified a common downstream protein, ubiquitin-C, extensively interconnected with ALS-causative proteins (22 out of 24) which was not linked to ALS previously. Our in silico approach provides the computational background for identifying ALS therapeutic targets, and points out the potential downstream common ground of ALS-causative mutations.

Evaluation of the sensitizing potential of food proteins using two mouse models.

PubMed

Smit, Joost; Zeeuw-Brouwer, Mary-Lène de; van Roest, Manon; de Jong, Govardus; van Bilsen, Jolanda

2016-11-16

The current methodology to identify allergenic food proteins is effective in identifying those that are likely to cross-react with known allergens. However, most assays show false positive results for low/non-allergens. Therefore, an ex vivo/in vitro DC-T cell assay and an in vivo mouse model were used to distinguish known allergenic food proteins (Ara h 1, β-Lactoglobulin, Pan b 1, bovine serum albumin, whey protein isolate) from low/non allergenic food proteins (soy lipoxygenase, gelatin, beef tropomyosin, rubisco, Sola t 1). CD4+ T cells from protein/alum-immunized mice were incubated with corresponding protein-pulsed bone marrow-derived DC and analyzed for cytokine release. All known allergens induced Th2 responses in vitro, whereas soy lipoxygenase, gelatin or beef tropomyosin did not. Sola t 1 and rubisco induced a more generalized T cell response due to endotoxin contamination, indicating the endotoxin-sensitivity of the DC-T assay. To analyze responses in vivo, mice were orally sensitized on days 0 and 7. Known allergens induced IgE and mMCP-1 release upon oral challenge at day 16, whereas the low/non-allergens did not. Both the DC-T cell assay and the mouse model were able to distinguish 5 known allergens from 5 low/non-allergens and may be useful to identify novel allergenic food proteins. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Building a knowledge-based statistical potential by capturing high-order inter-residue interactions and its applications in protein secondary structure assessment.

PubMed

Li, Yaohang; Liu, Hui; Rata, Ionel; Jakobsson, Eric

2013-02-25

The rapidly increasing number of protein crystal structures available in the Protein Data Bank (PDB) has naturally made statistical analyses feasible in studying complex high-order inter-residue correlations. In this paper, we report a context-based secondary structure potential (CSSP) for assessing the quality of predicted protein secondary structures generated by various prediction servers. CSSP is a sequence-position-specific knowledge-based potential generated based on the potentials of mean force approach, where high-order inter-residue interactions are taken into consideration. The CSSP potential is effective in identifying secondary structure predictions with good quality. In 56% of the targets in the CB513 benchmark, the optimal CSSP potential is able to recognize the native secondary structure or a prediction with Q3 accuracy higher than 90% as best scored in the predicted secondary structures generated by 10 popularly used secondary structure prediction servers. In more than 80% of the CB513 targets, the predicted secondary structures with the lowest CSSP potential values yield higher than 80% Q3 accuracy. Similar performance of CSSP is found on the CASP9 targets as well. Moreover, our computational results also show that the CSSP potential using triplets outperforms the CSSP potential using doublets and is currently better than the CSSP potential using quartets.

Analysis of potential protein-modifying variants in 9000 endometriosis patients and 150000 controls of European ancestry.

PubMed

Sapkota, Yadav; Vivo, Immaculata De; Steinthorsdottir, Valgerdur; Fassbender, Amelie; Bowdler, Lisa; Buring, Julie E; Edwards, Todd L; Jones, Sarah; O, Dorien; Peterse, Daniëlle; Rexrode, Kathryn M; Ridker, Paul M; Schork, Andrew J; Thorleifsson, Gudmar; Wallace, Leanne M; Kraft, Peter; Morris, Andrew P; Nyholt, Dale R; Edwards, Digna R Velez; Nyegaard, Mette; D'Hooghe, Thomas; Chasman, Daniel I; Stefansson, Kari; Missmer, Stacey A; Montgomery, Grant W

2017-09-12

Genome-wide association (GWA) studies have identified 19 independent common risk loci for endometriosis. Most of the GWA variants are non-coding and the genes responsible for the association signals have not been identified. Herein, we aimed to assess the potential role of protein-modifying variants in endometriosis using exome-array genotyping in 7164 cases and 21005 controls, and a replication set of 1840 cases and 129016 controls of European ancestry. Results in the discovery sample identified significant evidence for association with coding variants in single-variant (rs1801232-CUBN) and gene-level (CIITA and PARP4) meta-analyses, but these did not survive replication. In the combined analysis, there was genome-wide significant evidence for rs13394619 (P = 2.3 × 10 -9 ) in GREB1 at 2p25.1 - a locus previously identified in a GWA meta-analysis of European and Japanese samples. Despite sufficient power, our results did not identify any protein-modifying variants (MAF > 0.01) with moderate or large effect sizes in endometriosis, although these variants may exist in non-European populations or in high-risk families. The results suggest continued discovery efforts should focus on genotyping large numbers of surgically-confirmed endometriosis cases and controls, and/or sequencing high-risk families to identify novel rare variants to provide greater insights into the molecular pathogenesis of the disease.

Postproduction Handling and Administration of Protein Pharmaceuticals and Potential Instability Issues.

PubMed

Nejadnik, M Reza; Randolph, Theodore W; Volkin, David B; Schöneich, Christian; Carpenter, John F; Crommelin, Daan J A; Jiskoot, Wim

2018-04-14

The safety and efficacy of protein pharmaceuticals depend not only on biological activity but also on purity levels. Impurities may be process related because of limitations in manufacturing or product related because of protein degradation occurring throughout the life history of a product. Although the pharmaceutical biotechnology industry has made great progress in improving bulk and drug product manufacturing as well as company-controlled storage and transportation conditions to minimize the level of degradation, there is less control over the many factors that may subsequently affect product quality after the protein pharmaceuticals are released and shipped by the manufacturer. Routine handling or unintentional mishandling of therapeutic protein products may cause protein degradation that remains unnoticed but can potentially compromise the clinical safety and efficacy of the product. In this commentary, we address some potential risks associated with (mis)handling of protein pharmaceuticals after release by the manufacturer. We summarize the environmental stress factors that have been shown to cause protein degradation and that may be encountered during typical handling procedures of protein pharmaceuticals in a hospital setting or during self-administration by patients. Moreover, we provide recommendations for improvements in product handling to help ensure the quality of protein pharmaceuticals during use. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

[HMGA proteins and their genes as a potential neoplastic biomarkers].

PubMed

Balcerczak, Ewa; Balcerczak, Mariusz; Mirowski, Marek

2005-01-01

HMGA proteins and their genes are described in this article. HMGA proteins reveal ability to bind DNA in AT-rich regions, which are characteristic for gene promoter sequences. This interaction lead to gene silencing or their overexpression. In normal tissue HMGA proteins level is low or even undetectable. During embriogenesis their level is increasing. High HMGA proteins level is characteristic for tumor phenotype of spontaneous and experimental malignant neoplasms. High HMGA proteins expression correlate with bad prognostic factors and with metastases formation. HMGA genes expression can be used as a marker of tumor progression. Present studies connected with tumor gene therapy based on HMGA proteins sythesis inhibition by the use of viral vectors containing gene encoding these proteins in antisence orientation, as well as a new potential anticancer drugs acting as crosslinkers between DNA and HMGA proteins suggest their usefulness as a targets in cancer therapy.

Clonal analyses and gene profiling identify genetic biomarkers of the thermogenic potential of human brown and white preadipocytes.

PubMed

Xue, Ruidan; Lynes, Matthew D; Dreyfuss, Jonathan M; Shamsi, Farnaz; Schulz, Tim J; Zhang, Hongbin; Huang, Tian Lian; Townsend, Kristy L; Li, Yiming; Takahashi, Hirokazu; Weiner, Lauren S; White, Andrew P; Lynes, Maureen S; Rubin, Lee L; Goodyear, Laurie J; Cypess, Aaron M; Tseng, Yu-Hua

2015-07-01

Targeting brown adipose tissue (BAT) content or activity has therapeutic potential for treating obesity and the metabolic syndrome by increasing energy expenditure. However, both inter- and intra-individual differences contribute to heterogeneity in human BAT and potentially to differential thermogenic capacity in human populations. Here we generated clones of brown and white preadipocytes from human neck fat and characterized their adipogenic and thermogenic differentiation. We combined an uncoupling protein 1 (UCP1) reporter system and expression profiling to define novel sets of gene signatures in human preadipocytes that could predict the thermogenic potential of the cells once they were maturated. Knocking out the positive UCP1 regulators, PREX1 and EDNRB, in brown preadipocytes using CRISPR-Cas9 markedly abolished the high level of UCP1 in brown adipocytes differentiated from the preadipocytes. Finally, we were able to prospectively isolate adipose progenitors with great thermogenic potential using the cell surface marker CD29. These data provide new insights into the cellular heterogeneity in human fat and offer potential biomarkers for identifying thermogenically competent preadipocytes.

Characterization of the porcine neonatal Fc receptor—potential use for trans-epithelial protein delivery

PubMed Central

Stirling, Catrina M A; Charleston, Bryan; Takamatsu, Haru; Claypool, Steven; Lencer, Wayne; Blumberg, Richard S; Wileman, Thomas E

2005-01-01

The neonatal Fc receptor transports maternal immunoglobulin across the gut wall and has the potential to deliver genetically engineered proteins bearing immunoglobulin Fc domains across the gut to the mucosal immune system. Here we have characterized the porcine neonatal Fc receptor and tested its utility as a model system to study this kind of protein delivery. The complete DNA sequence obtained from an EST revealed 70–80% homology to mouse and human receptors, respectively, and tyrptophan and di-leucine endocytosis motifs were identified in the cytoplasmic tail. Reverse transcription–polymerase chain reaction analysis showed expression of the receptor mRNA in gut, liver, kidney and spleen tissue, aortic endothelial cells and monocytes. Pig kidney cell lines showed saturable pH-dependent binding and uptake of porcine immunoglobulin G (IgG) and also bovine, mouse and human IgG. Polyclonal antibodies raised against the receptor immunoprecipitated a protein of 40 000 MW when the cDNA was expressed in cells and the receptor required assembly with porcine β2-microglobulin for transport from the endoplasmic reticulum to recycling and early endosomes. Immunohistochemical analysis showed the receptor expressed in epithelial cells of the gut of young and adult animals. The ability of the receptor to deliver immunoglobulin across the gut was demonstrated by feeding piglets bovine colostrum as a source of bovine IgG. Bovine IgG was delivered into the pig circulation. Pigs express the neonatal Fc receptor and the receptor has the potential to deliver protein antigens to the pig immune system. PMID:15804291

Identifying biological concepts from a protein-related corpus with a probabilistic topic model

PubMed Central

Zheng, Bin; McLean, David C; Lu, Xinghua

2006-01-01

Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO) terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text. PMID:16466569

Theoretical models for electrochemical impedance spectroscopy and local ζ-potential of unfolded proteins in nanopores

NASA Astrophysics Data System (ADS)

Vitarelli, Michael J.; Talaga, David S.

2013-09-01

Single solid-state nanopores find increasing use for electrical detection and/or manipulation of macromolecules. These applications exploit the changes in signals due to the geometry and electrical properties of the molecular species found within the nanopore. The sensitivity and resolution of such measurements are also influenced by the geometric and electrical properties of the nanopore. This paper continues the development of an analytical theory to predict the electrochemical impedance spectra of nanopores by including the influence of the presence of an unfolded protein using the variable topology finite Warburg impedance model previously published by the authors. The local excluded volume of, and charges present on, the segment of protein sampled by the nanopore are shown to influence the shape and peak frequency of the electrochemical impedance spectrum. An analytical theory is used to relate the capacitive response of the electrical double layer at the surface of the protein to both the charge density at the protein surface and the more commonly measured zeta potential. Illustrative examples show how the theory predicts that the varying sequential regions of surface charge density and excluded volume dictated by the protein primary structure may allow for an impedance-based approach to identifying unfolded proteins.

Immunoblotting Quantification Approach for Identifying Potential Hypoallergenic Citrus Cultivars.

PubMed

Wu, Jinlong; Deng, Wenjun; Lin, Dingbo; Deng, Xiuxin; Ma, Zhaocheng

2018-02-28

The inherent allergens of citrus fruits, such as Cit s 1, Cit s 2, Cit s 3 can cause allergic reactions. A better understanding of the genetic factors (cultivar to cultivar) affecting the allergenic potential of citrus fruits would be beneficial for further identification of hypoallergenic genotypes. In the present study, an immunoblotting quantification approach was adopted to assess the potential allergenicity of 21 citrus cultivars, including nine subgroups (tangerine, satsuma, orange, pummelo, grapefruit, lemon, kumquat, tangor, and tangelo). To prepare highly sensitive and specific rabbit polyclonal antibodies, antigenicity of purified rCit s 1.01, rCit s 2.01, and rCit s 3.01 peptides were enhanced with high epitope density in a single protein molecule. The data integration of three citrus allergen quantifications demonstrated that the four pummelo cultivars (Kao Phuang Pummelo, Wanbai Pummelo, Shatian Pummelo, and Guanxi Pummelo) were potential hypoallergenic, compared with other 8 subgroups. Moreover, the immunological analyses with sera of allergic subjects revealed that Shatian Pummelo and Guanxi Pummelo showed the lowest immunoreactivity in 8 representative citrus cultivars. These potential hypoallergenic genotypes are of great significance to not only allergic consumers but also citrus breeders in the genetic improvement of hypoallergenic citrus as breeding resources.

Prolonged Fasting Identifies Heat Shock Protein 10 as a Sirtuin 3 Substrate

PubMed Central

Lu, Zhongping; Chen, Yong; Aponte, Angel M.; Battaglia, Valentina; Gucek, Marjan; Sack, Michael N.

2015-01-01

Although Sirtuin 3 (SIRT3), a mitochondrially enriched deacetylase and activator of fat oxidation, is down-regulated in response to high fat feeding, the rate of fatty acid oxidation and mitochondrial protein acetylation are invariably enhanced in this dietary milieu. These paradoxical data implicate that additional acetylation modification-dependent levels of regulation may be operational under nutrient excess conditions. Because the heat shock protein (Hsp) Hsp10-Hsp60 chaperone complex mediates folding of the fatty acid oxidation enzyme medium-chain acyl-CoA dehydrogenase, we tested whether acetylation-dependent mitochondrial protein folding contributes to this regulatory discrepancy. We demonstrate that Hsp10 is a functional SIRT3 substrate and that, in response to prolonged fasting, SIRT3 levels modulate mitochondrial protein folding. Acetyl mutagenesis of Hsp10 lysine 56 alters Hsp10-Hsp60 binding, conformation, and protein folding. Consistent with Hsp10-Hsp60 regulation of fatty acid oxidation enzyme integrity, medium-chain acyl-CoA dehydrogenase activity and fat oxidation are elevated by Hsp10 acetylation. These data identify acetyl modification of Hsp10 as a nutrient-sensing regulatory node controlling mitochondrial protein folding and metabolic function. PMID:25505263

An RNAi Screen To Identify Protein Phosphatases That Function Within the Drosophila Circadian Clock.

PubMed

Agrawal, Parul; Hardin, Paul E

2016-12-07

Circadian clocks in eukaryotes keep time via cell-autonomous transcriptional feedback loops. A well-characterized example of such a transcriptional feedback loop is in Drosophila, where CLOCK-CYCLE (CLK-CYC) complexes activate transcription of period (per) and timeless (tim) genes, rising levels of PER-TIM complexes feed-back to repress CLK-CYC activity, and degradation of PER and TIM permits the next cycle of CLK-CYC transcription. The timing of CLK-CYC activation and PER-TIM repression is regulated posttranslationally, in part through rhythmic phosphorylation of CLK, PER, and TIM. Previous behavioral screens identified several kinases that control CLK, PER, and TIM levels, subcellular localization, and/or activity, but two phosphatases that function within the clock were identified through the analysis of candidate genes from other pathways or model systems. To identify phosphatases that play a role in the clock, we screened clock cell-specific RNA interference (RNAi) knockdowns of all annotated protein phosphatases and protein phosphatase regulators in Drosophila for altered activity rhythms. This screen identified 19 protein phosphatases that lengthened or shortened the circadian period by ≥1 hr (p ≤ 0.05 compared to controls) or were arrhythmic. Additional RNAi lines, transposon inserts, overexpression, and loss-of-function mutants were tested to independently confirm these RNAi phenotypes. Based on genetic validation and molecular analysis, 15 viable protein phosphatases remain for future studies. These candidates are expected to reveal novel features of the circadian timekeeping mechanism in Drosophila that are likely to be conserved in all animals including humans. Copyright © 2016 Agrawal and Hardin.

UDoNC: An Algorithm for Identifying Essential Proteins Based on Protein Domains and Protein-Protein Interaction Networks.

PubMed

Peng, Wei; Wang, Jianxin; Cheng, Yingjiao; Lu, Yu; Wu, Fangxiang; Pan, Yi

2015-01-01

Prediction of essential proteins which are crucial to an organism's survival is important for disease analysis and drug design, as well as the understanding of cellular life. The majority of prediction methods infer the possibility of proteins to be essential by using the network topology. However, these methods are limited to the completeness of available protein-protein interaction (PPI) data and depend on the network accuracy. To overcome these limitations, some computational methods have been proposed. However, seldom of them solve this problem by taking consideration of protein domains. In this work, we first analyze the correlation between the essentiality of proteins and their domain features based on data of 13 species. We find that the proteins containing more protein domain types which rarely occur in other proteins tend to be essential. Accordingly, we propose a new prediction method, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network. In UDoNC, the essentiality of proteins is decided by the number and the frequency of their protein domain types, as well as the essentiality of their adjacent edges measured by edge clustering coefficient. The experimental results on S. cerevisiae data show that UDoNC outperforms other existing methods in terms of area under the curve (AUC). Additionally, UDoNC can also perform well in predicting essential proteins on data of E. coli.

Fast tandem mass spectra-based protein identification regardless of the number of spectra or potential modifications examined.

PubMed

Falkner, Jayson; Andrews, Philip

2005-05-15

Comparing tandem mass spectra (MSMS) against a known dataset of protein sequences is a common method for identifying unknown proteins; however, the processing of MSMS by current software often limits certain applications, including comprehensive coverage of post-translational modifications, non-specific searches and real-time searches to allow result-dependent instrument control. This problem deserves attention as new mass spectrometers provide the ability for higher throughput and as known protein datasets rapidly grow in size. New software algorithms need to be devised in order to address the performance issues of conventional MSMS protein dataset-based protein identification. This paper describes a novel algorithm based on converting a collection of monoisotopic, centroided spectra to a new data structure, named 'peptide finite state machine' (PFSM), which may be used to rapidly search a known dataset of protein sequences, regardless of the number of spectra searched or the number of potential modifications examined. The algorithm is verified using a set of commercially available tryptic digest protein standards analyzed using an ABI 4700 MALDI TOFTOF mass spectrometer, and a free, open source PFSM implementation. It is illustrated that a PFSM can accurately search large collections of spectra against large datasets of protein sequences (e.g. NCBI nr) using a regular desktop PC; however, this paper only details the method for identifying peptide and subsequently protein candidates from a dataset of known protein sequences. The concept of using a PFSM as a peptide pre-screening technique for MSMS-based search engines is validated by using PFSM with Mascot and XTandem. Complete source code, documentation and examples for the reference PFSM implementation are freely available at the Proteome Commons, http://www.proteomecommons.org and source code may be used both commercially and non-commercially as long as the original authors are credited for their work.

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

PubMed

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Bioinformatics analysis to assess potential risks of allergenicity and toxicity of HRAP and PFLP proteins in genetically modified bananas resistant to Xanthomonas wilt disease.

PubMed

Jin, Yuan; Goodman, Richard E; Tetteh, Afua O; Lu, Mei; Tripathi, Leena

2017-11-01

Banana Xanthomonas wilt (BXW) disease threatens banana production and food security throughout East Africa. Natural resistance is lacking among common cultivars. Genetically modified (GM) bananas resistant to BXW disease were developed by inserting the hypersensitive response-assisting protein (Hrap) or/and the plant ferredoxin-like protein (Pflp) gene(s) from sweet pepper (Capsicum annuum). Several of these GM banana events showed 100% resistance to BXW disease under field conditions in Uganda. The current study evaluated the potential allergenicity and toxicity of the expressed proteins HRAP and PFLP based on evaluation of published information on the history of safe use of the natural source of the proteins as well as established bioinformatics sequence comparison methods to known allergens (www.AllergenOnline.org and NCBI Protein) and toxins (NCBI Protein). The results did not identify potential risks of allergy and toxicity to either HRAP or PFLP proteins expressed in the GM bananas that might suggest potential health risks to humans. We recognize that additional tests including stability of these proteins in pepsin assay, nutrient analysis and possibly an acute rodent toxicity assay may be required by national regulatory authorities. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Proteomic analysis of processing by-products from canned and fresh tuna: identification of potentially functional food proteins.

PubMed

Sanmartín, Esther; Arboleya, Juan Carlos; Iloro, Ibon; Escuredo, Kepa; Elortza, Felix; Moreno, F Javier

2012-09-15

Proteomic approaches have been used to identify the main proteins present in processing by-products generated by the canning tuna-industry, as well as in by-products derived from filleting of skeletal red muscle of fresh tuna. Following fractionation by using an ammonium sulphate precipitation method, three proteins (tropomyosin, haemoglobin and the stress-shock protein ubiquitin) were identified in the highly heterogeneous and heat-treated material discarded by the canning-industry. Additionally, this fractionation method was successful to obtain tropomyosin of high purity from the heterogeneous starting material. By-products from skeletal red muscle of fresh tuna were efficiently fractionated to sarcoplasmic and myofibrillar fractions, prior to the identification based mainly on the combined searching of the peptide mass fingerprint (MALDI-TOF) and peptide fragment fingerprinting (MALDI LIFT-TOF/TOF) spectra of fifteen bands separated by 1D SDS-PAGE. Thus, the sarcoplasmic fraction contained myoglobin and several enzymes that are essential for efficient energy production, whereas the myofibrillar fraction had important contractile proteins, such as actin, tropomyosin, myosin or an isoform of the enzyme creatine kinase. Application of proteomic technologies has revealed new knowledge on the composition of important by-products from tuna species, enabling a better evaluation of their potential applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Use of Event-Related Potentials to Identify Language and Reading Skills

ERIC Educational Resources Information Center

Molfese, Victoria J.; Molfese, Dennis L.; Beswick, Jennifer L.; Jacobi-Vessels, Jill; Molfese, Peter J.; Molnar, Andrew E.; Wagner, Mary C.; Haines, Brittany L.

2008-01-01

The extent to which oral language and emergent literacy skills are influenced by event-related potential measures of phonological processing was examined. Results revealed that event-related potential responses identify differences in letter naming but not receptive language skills.

Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

PubMed Central

2010-01-01

replication studies, and changes in these proteins following the initiation of hormone therapy use were shown to have potential to help explain hormone therapy effects on those diseases. Conclusions In-depth proteomic discovery analysis of prediagnostic plasma samples identified B2M and IGFBP4 as risk markers for CHD and stroke respectively, and provided a number of candidate markers of disease risk and candidate mediators of hormone therapy effects on CHD and stroke. Clinical Trials Registration ClinicalTrials.gov identifier: NCT00000611 PMID:20667078

Is myelin basic protein a potential biomarker of brain cancer?

PubMed

Zavialova, M G; Shevchenko, V E; Nikolaev, E N; Zgoda, V G

2017-08-01

Myelin basic protein is a potential biomarker for the central nervous system diseases in which the myelin sheath is destroyed. Using pseudo-selected reaction monitoring and the method of standard additions, we have measured the myelin basic protein level in the cerebrospinal fluid of patients with neurotrauma (n = 6), chronic neurodegenerative diseases (n = 2) and brain cancer (n = 5). Myelin basic protein was detected only in four out of five cerebrospinal fluid samples of patients with brain cancer. The cerebrospinal fluid myelin basic protein level ranged from 3.7 to 8.8 ng ml -1 . We suggest that monitoring of myelin basic protein in cerebrospinal fluid can serve as a diagnostic test for the brain cancer.

Identifying three-dimensional structures of autophosphorylation complexes in crystals of protein kinases

PubMed Central

Xu, Qifang; Malecka, Kimberly L.; Fink, Lauren; Jordan, E. Joseph; Duffy, Erin; Kolander, Samuel; Peterson, Jeffrey; Dunbrack, Roland L.

2016-01-01

Protein kinase autophosphorylation is a common regulatory mechanism in cell signaling pathways. Crystal structures of several homomeric protein kinase complexes have a serine, threonine, or tyrosine autophosphorylation site of one kinase monomer located in the active site of another monomer, a structural complex that we call an “autophosphorylation complex.” We developed and applied a structural bioinformatics method to identify all such autophosphorylation kinase complexes in X-ray crystallographic structures in the Protein Data Bank (PDB). We identified 15 autophosphorylation complexes in the PDB, of which 5 complexes had not previously been described in the publications describing the crystal structures. These 5 consist of tyrosine residues in the N-terminal juxtamembrane regions of colony stimulating factor 1 receptor (CSF1R, Tyr561) and EPH receptor A2 (EPHA2, Tyr594), tyrosine residues in the activation loops of the SRC kinase family member LCK (Tyr394) and insulin-like growth factor 1 receptor (IGF1R, Tyr1166), and a serine in a nuclear localization signal region of CDC-like kinase 2 (CLK2, Ser142). Mutations in the complex interface may alter autophosphorylation activity and contribute to disease; therefore we mutated residues in the autophosphorylation complex interface of LCK and found that two mutations impaired autophosphorylation (T445V and N446A) and mutation of Pro447 to Ala, Gly, or Leu increased autophosphorylation. The identified autophosphorylation sites are conserved in many kinases, suggesting that, by homology, these complexes may provide insight into autophosphorylation complex interfaces of kinases that are relevant drug targets. PMID:26628682

Epitope presentation is an important determinant of the utility of antigens identified from protein arrays in the development of autoantibody diagnostic assays.

PubMed

Murphy, Mairead A; O'Connell, David J; O'Kane, Sara L; O'Brien, John K; O'Toole, Sharon; Martin, Cara; Sheils, Orla; O'Leary, John J; Cahill, Dolores J

2012-08-03

Autoantibodies represent an attractive biomarker for diagnostic assays principally due to the stability of immunoglobulin in patient serum facilitating measurement with conventional assays. Immune responses to tumorigenesis may facilitate detection of ovarian cancer in the early stages of the disease with identification of a panel of tumour specific autoantibodies. Despite the reporting of many tumour associated autoantibodies using arrays of tumour antigens, this has not led to the advance in diagnostic capability as rapidly as was initially expected. Here we examine the potential diagnostic utility of candidate autoantibody biomarkers identified via screening of serum samples on a high content human protein array from a unique cohort of early stage and late stage ovarian cancer patients. We analyse the performance of autoantibodies to the tumour suppressor protein p53 and the novel autoantigens alpha adducin and endosulfine alpha identified in our array screen. Each antigen has different performance characteristics using conventional ELISA format and Western blot immunoassay. The high attrition rate of promising autoantigens identified by array screening can in part be explained by the presentation of the epitope of the antigen in the subsequent method of validation and this study provides directions on maximising the potential of candidate biomarkers. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Application of Effective Fragment Potential Methos to the Redox Potential of Green Fluorescent Protein

NASA Astrophysics Data System (ADS)

Ghosh, Debashree; Krylov, Anna I.

2011-06-01

Green fluorescent proteins (GFP) can be considered as a model for flurogenic dyes and are of importance in photovoltaic materials. It exhibits bright green fluorescence when exposed to blue light and has been an extremely powerful tool as non-invasive marker in living cells and extensibly used in molecular and cell biology. The understanding of the underlying electronic structure of these proteins and its chromophore is therefore crucial to the understanding of the mechanism for its optical properties. The chromophore of the GFP is p-hydroxybenzylidene-imidazolinone (HBDI) and is embedded in the center of the β barrel of the GFP. Calculating redox potential of this chromophore is a challenging problem, especially in diverse solvents and protein environment. It is possible to carry out high-level accurate ab-initio calculation of ionization potential or electron affinity of the microsolvated chromophore or the bare chromophore. But, it is not possible to extend these calculations to bulk solvents due to the high computational cost. Effective fragment potential (EFP)[1,2] method gives us a convenient tool to understand such systems. In our work, we have benchmarked the ionization energy and electron affinity of the microsolvated GFP chromophore calculated by combined EOM-IP-CCSD/EFP and EOM-EA-CCSD/EFP with the EOM-IP-CCSD and EOM-EA-CCSD calculations of the oxidized and reduced forms. We have carried out similar EFP-EOM-IP-CCSD and EFP-EOM-EA-CCSD calculations of ionization potential and electron affinity of GFP choromophore in bulk solvent generated by ab-initio molecular dynamics simulations. [1] M. S. Gordon, L. Slipchenko, H. Li, J. H. Jensen, Annual Reports in Computational Chemistry, Volume 3, 177 (2007). [2] D. Ghosh, D. Kosenkov, V. Vanovschi, C.F. Williams, J.M. Herbert, M.S. Gordon, M.W. Schmidt, L.V. Slipchenko, and A.I. Krylov, J. Phys. Chem. A 114, 12739 (2010).

Chromobacterium violaceum: important insights for virulence and biotechnological potential by exoproteomic studies.

PubMed

Ciprandi, Alessandra; da Silva, Wanderson Marques; Santos, Agenor Valadares; de Castro Pimenta, Adriano Monteiro; Carepo, Marta Sofia Peixe; Schneider, Maria Paula Cruz; Azevedo, Vasco; Silva, Artur

2013-07-01

Chromobacterium violaceum is a beta-proteobacterium with high biotechnological potential, found in tropical environments. This bacterium causes opportunistic infections in both humans and animals, that can spread throughout several tissues, quickly leading to the death of the host. Genomic studies identified potential mechanisms of pathogenicity but no further studies were done to confirm the expression of these systems. In this study 36 unique protein entries were identified in databank from a two-dimensional profile of C. violaceum secreted proteins. Chromobacterium violaceum exoproteomic preliminary studies confirmed the production of proteins identified as virulence factors (such as a collagenase, flagellum proteins, metallopeptidases, and toxins), allowing us to better understand its pathogenicity mechanisms. Biotechnologically interesting proteins (such as chitinase and chitosanase) were also identified among the secreted proteins, as well as proteins involved in the transport and capture of amino acids, carbohydrates, and oxidative stress protection. Overall, the secreted proteins identified provide us important insights on pathogenicity mechanisms, biotechnological potential, and environment adaptation of C. violaceum.

Characterization of the Raf kinase inhibitory protein (RKIP) binding pocket: NMR-based screening identifies small-molecule ligands.

PubMed

Shemon, Anne N; Heil, Gary L; Granovsky, Alexey E; Clark, Mathew M; McElheny, Dan; Chimon, Alexander; Rosner, Marsha R; Koide, Shohei

2010-05-05

Raf kinase inhibitory protein (RKIP), also known as phoshaptidylethanolamine binding protein (PEBP), has been shown to inhibit Raf and thereby negatively regulate growth factor signaling by the Raf/MAP kinase pathway. RKIP has also been shown to suppress metastasis. We have previously demonstrated that RKIP/Raf interaction is regulated by two mechanisms: phosphorylation of RKIP at Ser-153, and occupation of RKIP's conserved ligand binding domain with a phospholipid (2-dihexanoyl-sn-glycero-3-phosphoethanolamine; DHPE). In addition to phospholipids, other ligands have been reported to bind this domain; however their binding properties remain uncharacterized. In this study, we used high-resolution heteronuclear NMR spectroscopy to screen a chemical library and assay a number of potential RKIP ligands for binding to the protein. Surprisingly, many compounds previously postulated as RKIP ligands showed no detectable binding in near-physiological solution conditions even at millimolar concentrations. In contrast, we found three novel ligands for RKIP that specifically bind to the RKIP pocket. Interestingly, unlike the phospholipid, DHPE, these newly identified ligands did not affect RKIP binding to Raf-1 or RKIP phosphorylation. One out of the three ligands displayed off target biological effects, impairing EGF-induced MAPK and metabolic activity. This work defines the binding properties of RKIP ligands under near physiological conditions, establishing RKIP's affinity for hydrophobic ligands and the importance of bulky aliphatic chains for inhibiting its function. The common structural elements of these compounds defines a minimal requirement for RKIP binding and thus they can be used as lead compounds for future design of RKIP ligands with therapeutic potential.

Novel seminal fluid proteins in the seed beetle Callosobruchus maculatus identified by a proteomic and transcriptomic approach.

PubMed

Bayram, H; Sayadi, A; Goenaga, J; Immonen, E; Arnqvist, G

2017-02-01

The seed beetle Callosobruchus maculatus is a significant agricultural pest and increasingly studied model of sexual conflict. Males possess genital spines that increase the transfer of seminal fluid proteins (SFPs) into the female body. As SFPs alter female behaviour and physiology, they are likely to modulate reproduction and sexual conflict in this species. Here, we identified SFPs using proteomics combined with a de novo transcriptome. A prior 2D-sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis identified male accessory gland protein spots that were probably transferred to the female at mating. Proteomic analysis of these spots identified 98 proteins, a majority of which were also present within ejaculates collected from females. Standard annotation workflows revealed common functional groups for SFPs, including proteases and metabolic proteins. Transcriptomic analysis found 84 transcripts differentially expressed between the sexes. Notably, genes encoding 15 proteins were highly expressed in male abdomens and only negligibly expressed within females. Most of these sequences corresponded to 'unknown' proteins (nine of 15) and may represent rapidly evolving SFPs novel to seed beetles. Our combined analyses highlight 44 proteins for which there is strong evidence that they are SFPs. These results can inform further investigation, to better understand the molecular mechanisms of sexual conflict in seed beetles. © 2016 The Royal Entomological Society.

Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signaling.

PubMed

Muthamilarasan, Mehanathan; Bonthala, Venkata S; Khandelwal, Rohit; Jaishankar, Jananee; Shweta, Shweta; Nawaz, Kashif; Prasad, Manoj

2015-01-01

Transcription factors (TFs) are major players in stress signaling and constitute an integral part of signaling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4model plants, Setaria italica (SiWRKY) and S. viridis (SvWRKY), respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins that were computationally analyzed for their physicochemical properties. Sequence alignment and phylogenetic analysis classified these proteins into three major groups, namely I, II, and III with majority of WRKY proteins belonging to group II (53 SiWRKY and 23 SvWRKY), followed by group III (39 SiWRKY and 11 SvWRKY) and group I (10 SiWRKY and 6 SvWRKY). Group II proteins were further classified into 5 subgroups (IIa to IIe) based on their phylogeny. Domain analysis showed the presence of WRKY motif and zinc finger-like structures in these proteins along with additional domains in a few proteins. All SiWRKY genes were physically mapped on the S. italica genome and their duplication analysis revealed that 10 and 8 gene pairs underwent tandem and segmental duplications, respectively. Comparative mapping of SiWRKY and SvWRKY genes in related C4 panicoid genomes demonstrated the orthologous relationships between these genomes. In silico expression analysis of SiWRKY and SvWRKY genes showed their differential expression patterns in different tissues and stress conditions. Expression profiling of candidate SiWRKY genes in response to stress (dehydration and salinity) and hormone treatments (abscisic acid, salicylic acid, and methyl jasmonate) suggested the putative involvement of SiWRKY066 and SiWRKY082 in stress and hormone signaling. These genes could be potential candidates for further characterization to delineate their functional roles in abiotic stress signaling.

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks.

PubMed

Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques; Ferreira, Rafaela Salgado; Silva, Artur; Gromiha, Michael; Ghosh, Preetam; Barh, Debmalya; Azevedo, Vasco; Röttger, Richard

2016-11-04

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

Synthesis of 2,4,6-trichlorophenyl hydrazones and their inhibitory potential against glycation of protein.

PubMed

Khan, Khalid Mohammed; Shah, Zarbad; Ahmad, Viqar Uddin; Khan, Momin; Taha, Muhammad; Rahim, Fazal; Jahan, Humera; Perveen, Shahnaz; Choudhary, M Iqbal

2011-11-01

2,4,6-Trichlorophenyl hydrazones 1-35 were synthesized and their in vitro antiglycation potential was evaluated. Compounds 14 (IC50 = 27.2 ± 0.00 μM), and 18 (IC50 = 55.7 ± 0.00 μM) showed an excellent activity against glycation of protein, better than the standard (rutin, IC50 = 70 ± 0.50 μM). This study thus identified a novel series of antiglycation agents. A structure-activity relationship has been studied, and all the compounds were characterized by spectroscopic techniques.

Peripheral nerve proteins as potential autoantigens in acute and chronic inflammatory demyelinating polyneuropathies.

PubMed

Lim, Jia Pei; Devaux, Jérôme; Yuki, Nobuhiro

2014-10-01

Guillain-Barré syndrome is classified into acute inflammatory demyelinating polyneuropathy and acute motor axonal neuropathy. Whereas autoantibodies to GM1 or GD1a induce the development of acute motor axonal neuropathy, pathogenic autoantibodies have yet to be identified in acute inflammatory demyelinating polyneuropathy and chronic inflammatory demyelinating polyneuropathy. This review highlights the importance of autoantibodies to peripheral nerve proteins in the physiopathology of acute and chronic inflammatory demyelinating polyneuropathies. Moreover, we listed up other potential antigens, which may become helpful biomarkers for acquired, dysimmune demyelinating neuropathies based on their critical functions during myelination and their implications in hereditary demyelinating neuropathies. Copyright © 2014 Elsevier B.V. All rights reserved.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Computational prediction of host-pathogen protein-protein interactions.

PubMed

Dyer, Matthew D; Murali, T M; Sobral, Bruno W

2007-07-01

Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. Supplementary data are available at Bioinformatics online.

Development and optimization of a cell-based assay for the selection of synthetic compounds that potentiate bone morphogenetic protein-2 activity‡

PubMed Central

Okada, Motohiro; Sangadala, Sreedhara; Liu, Yunshan; Yoshida, Munehito; Reddy, Boojala Vijay B.; Titus, Louisa; Boden, Scott D.

2010-01-01

The requirement of large amounts of the recombinant human bone morphogenetic protein-2 (BMP-2) produces a huge translational barrier for its routine clinical use due to high cost. This leads to an urgent need to develop alternative methods to lower costs and/or increase efficacies for using BMP-2. In this study, we describe the development and optimization of a cell-based assay that is sensitive, reproducible, and reliable in identifying reagents that potentiate the effects of BMP-2 in inducing transdifferentiation of C2C12 myoblasts into the osteoblastic phenotype. The assay is based on a BMP-responsive Smad1-driven luciferase reporter gene. LIM mineralization protein-1 (LMP-1) is a novel intracellular LIM domain protein that has been shown by our group to enhance cellular responsiveness to BMP-2. Our previous report elucidated that the binding of LMP-1 with the WW2 domain in Smad ubiquitin regulatory factor-1 (Smurf1) rescues the osteogenic Smads from degradation. Here, using the optimized cell-based assay, we first evaluated the activity of the recombinantly prepared proteins, LMP-1, and its mutant (LMP-1ΔSmurf1) that lacks the Smurf1-WW2 domain-binding motif. Both the wild type and the mutant proteins were engineered to contain an 11-amino acid HIV-TAT protein derived membrane transduction domain to aid the cellular delivery of recombinant proteins. The cell-based reporter assay confirmed that LMP-1 potentiates the BMP-induced stimulation of C2C12 cells towards the osteoblastic phenotype. The potentiating effect of LMP-1 was significantly reduced when a specific-motif known to interact with Smurf1 was mutated. We validated the results obtained in the reporter assay by also monitoring the expression of mRNA for osteocalcin and alkaline phosphatase (ALP) which is widely accepted osteoblast differentiation marker genes. Finally, we provide further confirmation of our results by measuring the activity of alkaline phosphatase in support of the accuracy and

Development and optimization of a cell-based assay for the selection of synthetic compounds that potentiate bone morphogenetic protein-2 activity.

PubMed

Okada, Motohiro; Sangadala, Sreedhara; Liu, Yunshan; Yoshida, Munehito; Reddy, Boojala Vijay B; Titus, Louisa; Boden, Scott D

2009-12-01

The requirement of large amounts of the recombinant human bone morphogenetic protein-2 (BMP-2) produces a huge translational barrier for its routine clinical use due to high cost. This leads to an urgent need to develop alternative methods to lower costs and/or increase efficacies for using BMP-2. In this study, we describe the development and optimization of a cell-based assay that is sensitive, reproducible, and reliable in identifying reagents that potentiate the effects of BMP-2 in inducing transdifferentiation of C2C12 myoblasts into the osteoblastic phenotype. The assay is based on a BMP-responsive Smad1-driven luciferase reporter gene. LIM mineralization protein-1 (LMP-1) is a novel intracellular LIM domain protein that has been shown by our group to enhance cellular responsiveness to BMP-2. Our previous report elucidated that the binding of LMP-1 with the WW2 domain in Smad ubiquitin regulatory factor-1 (Smurf1) rescues the osteogenic Smads from degradation. Here, using the optimized cell-based assay, we first evaluated the activity of the recombinantly prepared proteins, LMP-1, and its mutant (LMP-1DeltaSmurf1) that lacks the Smurf1-WW2 domain-binding motif. Both the wild type and the mutant proteins were engineered to contain an 11-amino acid HIV-TAT protein derived membrane transduction domain to aid the cellular delivery of recombinant proteins. The cell-based reporter assay confirmed that LMP-1 potentiates the BMP-induced stimulation of C2C12 cells towards the osteoblastic phenotype. The potentiating effect of LMP-1 was significantly reduced when a specific-motif known to interact with Smurf1 was mutated. We validated the results obtained in the reporter assay by also monitoring the expression of mRNA for osteocalcin and alkaline phosphatase (ALP) which is widely accepted osteoblast differentiation marker genes. Finally, we provide further confirmation of our results by measuring the activity of alkaline phosphatase in support of the accuracy and

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Potential approaches for heterologous prion protein treatment of prion diseases

PubMed Central

Seelig, Davis M.; Goodman, Patricia A.; Skinner, Pamela J.

2016-01-01

ABSTRACT Prion diseases, or transmissible spongiform encephalopathies (TSEs) are progressive, fatal neurodegenerative diseases with no effective treatment. The pathology of these diseases involves the conversion of a protease sensitive form of the cellular prion protein (PrPC) into a protease resistant infectious form (PrPres). The efficiency of this conversion is predicated upon a number of factors, most notably a strong homology between cellular PrPC and PrPres. In our recently published study, we infected mice with the RML-Chandler strain of scrapie and treated them with heterologous hamster prion proteins. This treatment was seen to reduce clinical signs of prion disease, to delay the onset of clinical symptoms and to prolong survival. In this current article we discuss potential mechanisms of action of treatment with heterologous prion proteins. We also discuss potential extensions of these studies using a heterologous rabbit PrP-based treatment strategy or a peptide based strategy, and improvement of treatment delivery including a lentiviral-based system. PMID:26636482

Identifying potential kidney donors using social networking web sites.

PubMed

Chang, Alexander; Anderson, Emily E; Turner, Hang T; Shoham, David; Hou, Susan H; Grams, Morgan

2013-01-01

Social networking sites like Facebook may be a powerful tool for increasing rates of live kidney donation. They allow for wide dissemination of information and discussion and could lessen anxiety associated with a face-to-face request for donation. However, sparse data exist on the use of social media for this purpose. We searched Facebook, the most popular social networking site, for publicly available English-language pages seeking kidney donors for a specific individual, abstracting information on the potential recipient, characteristics of the page itself, and whether potential donors were tested. In the 91 pages meeting inclusion criteria, the mean age of potential recipients was 37 (range: 2-69); 88% were US residents. Other posted information included the individual's photograph (76%), blood type (64%), cause of kidney disease (43%), and location (71%). Thirty-two percent of pages reported having potential donors tested, and 10% reported receiving a live-donor kidney transplant. Those reporting donor testing shared more potential recipient characteristics, provided more information about transplantation, and had higher page traffic. Facebook is already being used to identify potential kidney donors. Future studies should focus on how to safely, ethically, and effectively use social networking sites to inform potential donors and potentially expand live kidney donation. © 2013 John Wiley & Sons A/S.

HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1*

PubMed Central

Hernandez, Anna; Buch, Anna; Sodeik, Beate; Cristea, Ileana Mihaela

2016-01-01

Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of

A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi

PubMed Central

2013-01-01

Background Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. Results We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F/WxC-motif from the barley powdery mildew pathogen. Application to the cereal pathogen Fusarium graminearum reveals a secreted phosphorylcholine phosphatase that is characteristic of hemibiotrophic and necrotrophic cereal pathogens and shares an ancient selection process with bacterial plant pathogens. Three F. graminearum protein clusters are found with an enriched secretion signal. One of these putative effector clusters contains proteins that share a [SG]-P-C-[KR]-P sequence motif in the N-terminal and show features not commonly associated with fungal effectors. This motif is conserved in secreted pathogenic Fusarium proteins and a prime candidate for functional testing. Conclusions Our pipeline has successfully uncovered conservation patterns, putative effectors and motifs of fungal pathogens that would have been overlooked by existing approaches that identify effectors as small, secreted, cysteine-rich peptides. It can be applied to any pathogenic proteome data, such as microbial pathogen data of plants and other organisms. PMID:24252298

Identifying and engineering promoters for high level and sustainable therapeutic recombinant protein production in cultured mammalian cells.

PubMed

Ho, Steven C L; Yang, Yuansheng

2014-08-01

Promoters are essential on plasmid vectors to initiate transcription of the transgenes when generating therapeutic recombinant proteins expressing mammalian cell lines. High and sustained levels of gene expression are desired during therapeutic protein production while gene expression is useful for cell engineering. As many finely controlled promoters exhibit cell and product specificity, new promoters need to be identified, optimized and carefully evaluated before use. Suitable promoters can be identified using techniques ranging from simple molecular biology methods to modern high-throughput omics screenings. Promoter engineering is often required after identification to either obtain high and sustained expression or to provide a wider range of gene expression. This review discusses some of the available methods to identify and engineer promoters for therapeutic recombinant protein expression in mammalian cells.

Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

PubMed

Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

2016-04-14

Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma.

PubMed

Chow, Yock Ping; Tan, Lu Ping; Chai, San Jiun; Abdul Aziz, Norazlin; Choo, Siew Woh; Lim, Paul Vey Hong; Pathmanathan, Rajadurai; Mohd Kornain, Noor Kaslina; Lum, Chee Lun; Pua, Kin Choo; Yap, Yoke Yeow; Tan, Tee Yong; Teo, Soo Hwang; Khoo, Alan Soo-Beng; Patel, Vyomesh

2017-03-03

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies.

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma

PubMed Central

Chow, Yock Ping; Tan, Lu Ping; Chai, San Jiun; Abdul Aziz, Norazlin; Choo, Siew Woh; Lim, Paul Vey Hong; Pathmanathan, Rajadurai; Mohd Kornain, Noor Kaslina; Lum, Chee Lun; Pua, Kin Choo; Yap, Yoke Yeow; Tan, Tee Yong; Teo, Soo Hwang; Khoo, Alan Soo-Beng; Patel, Vyomesh

2017-01-01

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies. PMID:28256603

Protein C: a potential biomarker in severe sepsis and a possible tool for monitoring treatment with drotrecogin alfa (activated)

PubMed Central

Shorr, Andrew F; Nelson, David R; Wyncoll, Duncan LA; Reinhart, Konrad; Brunkhorst, Frank; Vail, George Matthew; Janes, Jonathan

2008-01-01

Introduction Drotrecogin alfa (activated; DrotAA) treatment, a 96-hour infusion, reduces 28-day mortality in severe sepsis to approximately 25%. The question remains whether a longer infusion or higher dose could increase rate of survival. The goal of this study was to identify a dependable, sensitive measure with which to monitor disease progression and response in patients during DrotAA treatment. Methods Data on severe sepsis patients included in PROWESS (placebo-controlled, double-blind, randomized study of 850 DrotAA and 840 placebo individuals) and ENHANCE (single-arm, open-label study of 2,375 DrotAA patients) studies were analyzed. In these studies, DrotAA (24 μg/kg per hour) or placebo was infused for 96 hours and patients were followed for 28 days. Data on six laboratory measures and five organ dysfunctions were systematically analyzed to identify a potential surrogate end-point for monitoring DrotAA therapy and predicting 28-day mortality at the end of therapy. To allow comparison across variables, sensitivity and specificity analyses identified cut-off values for preferred outcome, and relative risks for being above or below cut-offs were calculated, as was the 'proportion of treatment effect explained' (PTEE) to identify biomarkers that contribute to benefit from DrotAA. Results Protein C was the only variable that correlated with outcome across all analyses. Using placebo data, a baseline protein C under 40% was established as a useful predictor of outcome (odds ratio 2.12). Similar odds ratios were associated with cut-off values of other biomarkers, but the treatment benefit associated with DrotAA was significantly greater below the cut-off than above the cut-off only for protein C (relative risk for 28-day mortality 0.66 versus 0.88; P = 0.04). Protein C was the only end-of-infusion biomarker that potentially explained at least 50% of the benefit from DrotAA (PTEE 57.2%). The PTEE was 41% for cardiovascular Sequential Organ Failure Assessment score

Recombinant small glutamine-rich tetratricopeptide repeat-containing protein of Leishmania infantum: Potential vaccine and diagnostic application against visceral leishmaniasis.

PubMed

Dias, Daniel S; Ribeiro, Patrícia A F; Martins, Vívian T; Lage, Daniela P; Portela, Áquila S B; Costa, Lourena E; Salles, Beatriz C S; Lima, Mariana P; Ramos, Fernanda F; Santos, Thaís T O; Caligiorne, Rachel B; Chávez-Fumagalli, Miguel A; Silveira, Julia A G; Magalhães-Soares, Danielle F; Gonçalves, Denise U; Oliveira, Jamil S; Roatt, Bruno M; Duarte, Mariana C; Menezes-Souza, Daniel; Silva, Eduardo S; Galdino, Alexsandro S; Machado-de-Ávila, Ricardo A; Teixeira, Antonio L; Coelho, Eduardo A F

2017-11-01

Different Leishmania proteins have been evaluated in order to find a potential vaccine candidate or diagnostic marker capable of providing long lasting protection against infection or helping to identify infected mammalian hosts, respectively. However, just few molecules have fulfilled all the requirements to be evaluated. In the current study, we evaluated the prophylactic and diagnostic value against visceral leishmaniasis (VL) of a small glutamine-rich tetratricopeptide repeat-containing (SGT) protein from Leishmania infantum species. In a first step, the immune response elicited by the immunization using the recombinant protein (rSGT) plus saponin was evaluated in BALB/c mice. Immunized animals had a low parasitism in all evaluated organs. They developed a specific Th1 immune response, which was based on protein-specific production of IFN-γ, IL-12 and GM-CSF, and a humoral response dominated by antibodies of the IgG2a isotype. Both CD4 + and CD8 + T cells contributed to the IFN-γ production, showing that both T cell subtypes contribute to the resistance against infection. Regarding its value as a diagnostic marker, rSGT showed maximum sensitivity and specificity to serologically identify L. infantum-infected dog and human sera. No cross-reactivity with sera from humans or dogs that had other diseases was found. Although further studies are necessary to validate these findings, data showed here suggest immunogenicity of rSGT and its protective effect against murine VL, as well as its potential for the serodiagnosis of human and canine VL. Copyright © 2017 Elsevier Ltd. All rights reserved.

An optimized magnetite microparticle-based phosphopeptide enrichment strategy for identifying multiple phosphorylation sites in an immunoprecipitated protein.

PubMed

Huang, Yi; Shi, Qihui; Tsung, Chia-Kuang; Gunawardena, Harsha P; Xie, Ling; Yu, Yanbao; Liang, Hongjun; Yang, Pengyuan; Stucky, Galen D; Chen, Xian

2011-01-01

To further improve the selectivity and throughput of phosphopeptide analysis for the samples from real-time cell lysates, here we demonstrate a highly efficient method for phosphopeptide enrichment via newly synthesized magnetite microparticles and the concurrent mass spectrometric analysis. The magnetite microparticles show excellent magnetic responsivity and redispersibility for a quick enrichment of those phosphopeptides in solution. The selectivity and sensitivity of magnetite microparticles in phosphopeptide enrichment are first evaluated by a known mixture containing both phosphorylated and nonphosphorylated proteins. Compared with the titanium dioxide-coated magnetic beads commercially available, our magnetite microparticles show a better specificity toward phosphopeptides. The selectively-enriched phosphopeptides from tryptic digests of β-casein can be detected down to 0.4 fmol μl⁻¹, whereas the recovery efficiency is approximately 90% for monophosphopeptides. This magnetite microparticle-based affinity technology with optimized enrichment conditions is then immediately applied to identify all possible phosphorylation sites on a signal protein isolated in real time from a stress-stimulated mammalian cell culture. A large fraction of peptides eluted from the magnetic particle enrichment step were identified and characterized as either single- or multiphosphorylated species by tandem mass spectrometry. With their high efficiency and utility for phosphopeptide enrichment, the magnetite microparticles hold great potential in the phosphoproteomic studies on real-time samples from cell lysates. Published by Elsevier Inc.

Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein-Protein Interfaces

PubMed Central

Zerbe, Brandon S.; Hall, David R.

2013-01-01

In the context of protein-protein interactions, the term “hot spot” refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening. PMID:22770357

Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.

PubMed

Zerbe, Brandon S; Hall, David R; Vajda, Sandor; Whitty, Adrian; Kozakov, Dima

2012-08-27

In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment-sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.

On the potential of using peculiarities of the protein intrinsic disorder distribution in mitochondrial cytochrome b to identify the source of animal meats

PubMed Central

Yacoub, Haitham A.; Sadek, Mahmoud A.; Uversky, Vladimir N.

2017-01-01

ABSTRACT This study was conducted to identify the source of animal meat based on the peculiarities of protein intrinsic disorder distribution in mitochondrial cytochrome b (mtCyt-b). The analysis revealed that animal and avian species can be discriminated based on the proportions of the two groups of residues, Leu+Ile, and Ser+Pro+Ala, in the amino acid sequences of their mtCyt-b. Although levels of the overall intrinsic disorder in mtCyt-b is not very high, the peculiarities of disorder distribution within the sequences of mtCyt-b from different species varies in a rather specific way. In fact, positions and intensities of disorder/flexibility “signals” in the corresponding disorder profiles are relatively unique for avian and animal species. Therefore, it is possible to devise a set of simple rules based on the peculiarities of disorder profiles of their mtCyt-b proteins to discriminate among species. This intrinsic disorder-based analysis represents a new technique that could be used to provide a promising solution for identification of the source of meats. PMID:28331777

Characterization of the Raf Kinase Inhibitory Protein (RKIP) Binding Pocket: NMR-Based Screening Identifies Small-Molecule Ligands

PubMed Central

Granovsky, Alexey E.; Clark, Mathew M.; McElheny, Dan; Chimon, Alexander; Rosner, Marsha R.; Koide, Shohei

2010-01-01

Background Raf kinase inhibitory protein (RKIP), also known as phoshaptidylethanolamine binding protein (PEBP), has been shown to inhibit Raf and thereby negatively regulate growth factor signaling by the Raf/MAP kinase pathway. RKIP has also been shown to suppress metastasis. We have previously demonstrated that RKIP/Raf interaction is regulated by two mechanisms: phosphorylation of RKIP at Ser-153, and occupation of RKIP's conserved ligand binding domain with a phospholipid (2-dihexanoyl-sn-glycero-3-phosphoethanolamine; DHPE). In addition to phospholipids, other ligands have been reported to bind this domain; however their binding properties remain uncharacterized. Methods/Findings In this study, we used high-resolution heteronuclear NMR spectroscopy to screen a chemical library and assay a number of potential RKIP ligands for binding to the protein. Surprisingly, many compounds previously postulated as RKIP ligands showed no detectable binding in near-physiological solution conditions even at millimolar concentrations. In contrast, we found three novel ligands for RKIP that specifically bind to the RKIP pocket. Interestingly, unlike the phospholipid, DHPE, these newly identified ligands did not affect RKIP binding to Raf-1 or RKIP phosphorylation. One out of the three ligands displayed off target biological effects, impairing EGF-induced MAPK and metabolic activity. Conclusions/Significance This work defines the binding properties of RKIP ligands under near physiological conditions, establishing RKIP's affinity for hydrophobic ligands and the importance of bulky aliphatic chains for inhibiting its function. The common structural elements of these compounds defines a minimal requirement for RKIP binding and thus they can be used as lead compounds for future design of RKIP ligands with therapeutic potential. PMID:20463977

Hidden Markov model approach for identifying the modular framework of the protein backbone.

PubMed

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

High throughput atmospheric pressure plasma-induced graft polymerization for identifying protein-resistant surfaces.

PubMed

Gu, Minghao; Kilduff, James E; Belfort, Georges

2012-02-01

Three critical aspects of searching for and understanding how to find highly resistant surfaces to protein adhesion are addressed here with specific application to synthetic membrane filtration. They include the (i) discovery of a series of previously unreported monomers from a large library of monomers with high protein resistance and subsequent low fouling characteristics for membrane ultrafiltration of protein-containing fluids, (ii) development of a new approach to investigate protein-resistant mechanisms from structure-property relationships, and (iii) adaptation of a new surface modification method, called atmospheric pressure plasma-induced graft polymerization (APP), together with a high throughput platform (HTP), for low cost vacuum-free synthesis of anti-fouling membranes. Several new high-performing chemistries comprising two polyethylene glycol (PEG), two amines and one zwitterionic monomers were identified from a library (44 commercial monomers) of five different classes of monomers as strong protein-resistant monomers. Combining our analysis here, using the Hansen solubility parameters (HSP) approach, and data from the literature, we conclude that strong interactions with water (hydrogen bonding) and surface flexibility are necessary for producing the highest protein resistance. Superior protein-resistant surfaces and subsequent anti-fouling performance was obtained with the HTP-APP as compared with our earlier HTP-photo graft-induced polymerization (PGP). Copyright © 2011 Elsevier Ltd. All rights reserved.

A reverse-phase protein microarray-based screen identifies host signaling dynamics upon Burkholderia spp. infection

PubMed Central

Chiang, Chih-Yuan; Uzoma, Ijeoma; Lane, Douglas J.; Memišević, Vesna; Alem, Farhang; Yao, Kuan; Kota, Krishna P.; Bavari, Sina; Wallqvist, Anders; Hakami, Ramin M.; Panchal, Rekha G.

2015-01-01

Burkholderia is a diverse genus of gram-negative bacteria that causes high mortality rate in humans, equines and cattle. The lack of effective therapeutic treatments poses serious public health threats. Developing insights toward host-Burkholderia spp. interaction is critical for understanding the pathogenesis of infection as well as identifying therapeutic targets for drug development. Reverse-phase protein microarray technology was previously proven to identify and characterize novel biomarkers and molecular signatures associated with infectious disease and cancer. In the present study, this technology was utilized to interrogate changes in host protein expression and phosphorylation events in macrophages infected with a collection of geographically diverse strains of Burkholderia spp. The expression or phosphorylation state of 25 proteins was altered during Burkholderia spp. infections of which eight proteins were selected for further characterization by immunoblotting. Increased phosphorylation of AMPK-α1, Src, and GSK3β suggested the importance of their roles in regulating Burkholderia spp. mediated innate immune response. Modulating the inflammatory response by perturbing their activities may provide therapeutic routes for future treatments. PMID:26284031

Differential proteomics analysis to identify proteins and pathways associated with male sterility of soybean using iTRAQ-based strategy.

PubMed

Li, Jiajia; Ding, Xianlong; Han, Shaohuai; He, Tingting; Zhang, Hao; Yang, Longshu; Yang, Shouping; Gai, Junyi

2016-04-14

To further elucidate the molecular mechanism of cytoplasmic male sterility (CMS) in soybean, a differential proteomic analysis was completed between the CMS line NJCMS1A and its maintainer NJCMS1B using iTRAQ-based strategy. As a result, 180 differential abundance proteins (DAPs) were identified, of which, 60 were down-regulated and 120 were up-regulated in NJCMS1A compared with NJCMS1B. Bioinformatic analysis showed that 167 DAPs were annotated in 41 Gene Ontology functional groups, 106 DAPs were classified into 20 clusters of orthologous groups of protein categories, and 128 DAPs were enrichment in 53 KEGG pathways. Fifteen differential level proteins/genes with the same expression pattern were identified in the further conjoint analysis of DAPs and the previously reported differential expression genes. Moreover, multiple reaction monitoring test, qRT-PCR analysis and enzyme activity assay validated that the iTRAQ results were reliable. Based on functional analysis of DAPs, we concluded that male sterility in NJCMS1A might be related to insufficiencies in energy supply, unbalance of protein synthesis and degradation, disruption of flavonoid synthesis, programmed cell death, abnormalities of substance metabolism, etc. These results might facilitate our understanding of the molecular mechanisms behind CMS in soybean. Soybean is an important global crop that provides protein and oil. Heterosis is a significantly potential approach to increase the yield of soybean. Cytoplasmic male sterility (CMS) plays a vital role in the production of hybrid seeds. However, the genetic and molecular mechanisms of male sterility in soybean still need to be further elucidated. In the present paper, a differential proteomic analysis was carried out and the results showed that several key proteins involved in key pathways were associated with male sterility in soybean. This work provides a new insight to understand the genetic and molecular mechanisms underlying CMS in soybean

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

PubMed

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and

Using a watershed-centric approach to identify potentially impacted beaches

EPA Science Inventory

Beaches can be affected by a variety of contaminants. Of particular concern are beaches impacted by human fecal contamination and urban runoff. This poster demonstrates a methodology to identify potentially impacted beaches using Geographic Information Systems (GIS). Since h...

Assessing the potential of atomistic molecular dynamics simulations to probe reversible protein-protein recognition and binding

PubMed Central

Abriata, Luciano A.; Dal Peraro, Matteo

2015-01-01

Protein-protein recognition and binding are governed by diffusion, noncovalent forces and conformational flexibility, entangled in a way that only molecular dynamics simulations can dissect at high resolution. Here we exploited ubiquitin’s noncovalent dimerization equilibrium to assess the potential of atomistic simulations to reproduce reversible protein-protein binding, by running submicrosecond simulations of systems with multiple copies of the protein at millimolar concentrations. The simulations essentially fail because they lead to aggregates, yet they reproduce some specificity in the binding interfaces as observed in known covalent and noncovalent ubiquitin dimers. Following similar observations in literature we hint at electrostatics and water descriptions as the main liable force field elements, and propose that their optimization should consider observables relevant to multi-protein systems and unfolded proteins. Within limitations, analysis of binding events suggests salient features of protein-protein recognition and binding, to be retested with improved force fields. Among them, that specific configurations of relative direction and orientation seem to trigger fast binding of two molecules, even over 50 Å distances; that conformational selection can take place within surface-to-surface distances of 10 to 40 Å i.e. well before actual intermolecular contact; and that establishment of contacts between molecules further locks their conformations and relative orientations. PMID:26023027

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes.

PubMed

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-05-26

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes.

Systematic analysis of mutation distribution in three dimensional protein structures identifies cancer driver genes

PubMed Central

Fujimoto, Akihiro; Okada, Yukinori; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Taniguchi, Hiroaki; Nakagawa, Hidewaki

2016-01-01

Protein tertiary structure determines molecular function, interaction, and stability of the protein, therefore distribution of mutation in the tertiary structure can facilitate the identification of new driver genes in cancer. To analyze mutation distribution in protein tertiary structures, we applied a novel three dimensional permutation test to the mutation positions. We analyzed somatic mutation datasets of 21 types of cancers obtained from exome sequencing conducted by the TCGA project. Of the 3,622 genes that had ≥3 mutations in the regions with tertiary structure data, 106 genes showed significant skew in mutation distribution. Known tumor suppressors and oncogenes were significantly enriched in these identified cancer gene sets. Physical distances between mutations in known oncogenes were significantly smaller than those of tumor suppressors. Twenty-three genes were detected in multiple cancers. Candidate genes with significant skew of the 3D mutation distribution included kinases (MAPK1, EPHA5, ERBB3, and ERBB4), an apoptosis related gene (APP), an RNA splicing factor (SF1), a miRNA processing factor (DICER1), an E3 ubiquitin ligase (CUL1) and transcription factors (KLF5 and EEF1B2). Our study suggests that systematic analysis of mutation distribution in the tertiary protein structure can help identify cancer driver genes. PMID:27225414

Role of surface layer collagen binding protein from indigenous Lactobacillus plantarum 91 in adhesion and its anti-adhesion potential against gut pathogen.

PubMed

Yadav, Ashok Kumar; Tyagi, Ashish; Kaushik, Jai Kumar; Saklani, Asha Chandola; Grover, Sunita; Batish, Virender Kumar

2013-12-14

Human feacal isolates were ascertain as genus Lactobacillus using specific primer LbLMA1/R16-1 and further identified as Lactobacillus plantarum with species specific primers Lpl-3/Lpl-2. 25 L. plantarum strains were further assessed for hydrophobicity following the microbial adhesion to hydrocarbons (MATH) method and colonization potentials based on their adherence to immobilized human collagen type-1. Surface proteins were isolated from selected L. plantarum 91(Lp91) strain. The purified collagen binding protein (Cbp) protein was assessed for its anti-adhesion activity against enteric Escherichia coli 0157:H7 pathogen on immobilized collagen. Four L. plantarum strains displayed high degree of hydrophobicity and significant adhesion to collagen. A 72 kDa protein was purified which reduced 59.71% adhesion of E. coli 0157:H7 on immobilized collagen as compared to control well during adhesion assay. Cbp protein is the major influencing factor in inhibition of E. coli 0157:H7 adhesion with extracellular matrix (ECM) components. Hydrophobicity and adhesion potential are closely linked attributes precipitating in better colonization potential of the lactobacillus strains. Cbp is substantiated as a crucial surface protein contributing in adhesion of lactobacillus strains. The study can very well be the platform for commercialization of indigenous probiotic strain once their functional attributes are clinically explored. Copyright © 2013 Elsevier GmbH. All rights reserved.

Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

PubMed

Núñez-Vivanco, Gabriel; Valdés-Jiménez, Alejandro; Besoaín, Felipe; Reyes-Parada, Miguel

2016-01-01

Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q-Exactive HF Mass Spectrometer.

PubMed

Wei, Wei; Luo, Weijia; Wu, Feilin; Peng, Xuehui; Zhang, Yao; Zhang, Manli; Zhao, Yan; Su, Na; Qi, YingZi; Chen, Lingsheng; Zhang, Yangjun; Wen, Bo; He, Fuchu; Xu, Ping

2016-11-04

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092.

Assessment of indigenous Nepalese soybean as a potential germplasm resource for improvement of protein in North American cultivars.

PubMed

Krishnan, Hari B; Natarajan, Savithiry S; Mahmoud, Ahmed A; Bennett, John O; Krishnan, Ammulu Hari; Prasad, Braj Nandan

2006-07-26

Soybeans contain approximately 40% protein and 20% oil and represents an important source of protein in animal rations and human diets. Attempts are being made to increase further the overall protein content of soybeans by utilization of exotic germplasms. In this study, soybean cultivars from Nepal have been characterized and their potential as a germplasm resource for improvement of the protein content and quality of North American cultivars assessed. Soybean cultivars 'Sathia', 'Seti', 'Kavre', and 'Soida Chiny', indigenous to various regions of Nepal, contained 42-45% protein, which is significantly higher in comparison to that of the North American cultivar 'Williams 82' (39%). Fractionation of seed protein by high-resolution two-dimensional gel electrophoresis revealed differences in the protein profiles of these cultivars. Various isoelectric forms of glycinin and beta-conglycinin were identified by comparing the matrix-assisted laser desorption ionization time-of-flight mass fingerprinting data against the National Center for Biotechnology Information nonredundant database. Nepalese cultivar Sathia was distinct, lacking some isoelectric forms of acidic and basic glycinin subunits while expressing other unique forms. The contribution of these unique protein spots present in either Sathia or Williams 82 to the total protein content was quantified using scanning laser densitometry. Distinct restriction fragment length polymorphisms (RFLP) for group 1 glycinin genes were observed among the tested Nepalese genotypes, indicating sequence variation among the cultivars. Conversely, evaluation of RFLP for the genes encoding group 2 glycinins, beta-conglycinin, and Bowman-Birk proteinase inhibitors indicated a high degree of conservation in these genes. Determination of amino acid composition, a reflection of protein quality, indicated that the arginine content of the Nepalese soybeans ranged from 7.7 to 8.1%, which was 5-10% higher than the 7.4% expressed in

Analysis of evolutionary conservation patterns and their influence on identifying protein functional sites.

PubMed

Fang, Chun; Noguchi, Tamotsu; Yamana, Hayato

2014-10-01

Evolutionary conservation information included in position-specific scoring matrix (PSSM) has been widely adopted by sequence-based methods for identifying protein functional sites, because all functional sites, whether in ordered or disordered proteins, are found to be conserved at some extent. However, different functional sites have different conservation patterns, some of them are linear contextual, some of them are mingled with highly variable residues, and some others seem to be conserved independently. Every value in PSSMs is calculated independently of each other, without carrying the contextual information of residues in the sequence. Therefore, adopting the direct output of PSSM for prediction fails to consider the relationship between conservation patterns of residues and the distribution of conservation scores in PSSMs. In order to demonstrate the importance of combining PSSMs with the specific conservation patterns of functional sites for prediction, three different PSSM-based methods for identifying three kinds of functional sites have been analyzed. Results suggest that, different PSSM-based methods differ in their capability to identify different patterns of functional sites, and better combining PSSMs with the specific conservation patterns of residues would largely facilitate the prediction.

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through

Identifying relationships between unrelated pharmaceutical target proteins on the basis of shared active compounds.

PubMed

Miljković, Filip; Kunimoto, Ryo; Bajorath, Jürgen

2017-08-01

Computational exploration of small-molecule-based relationships between target proteins from different families. Target annotations of drugs and other bioactive compounds were systematically analyzed on the basis of high-confidence activity data. A total of 286 novel chemical links were established between distantly related or unrelated target proteins. These relationships involved a total of 1859 bioactive compounds including 147 drugs and 141 targets. Computational analysis of large amounts of compounds and activity data has revealed unexpected relationships between diverse target proteins on the basis of compounds they share. These relationships are relevant for drug discovery efforts. Target pairs that we have identified and associated compound information are made freely available.

Global analysis of WRKY transcription factor superfamily in Setaria identifies potential candidates involved in abiotic stress signaling

PubMed Central

Muthamilarasan, Mehanathan; Bonthala, Venkata S.; Khandelwal, Rohit; Jaishankar, Jananee; Shweta, Shweta; Nawaz, Kashif; Prasad, Manoj

2015-01-01

Transcription factors (TFs) are major players in stress signaling and constitute an integral part of signaling networks. Among the major TFs, WRKY proteins play pivotal roles in regulation of transcriptional reprogramming associated with stress responses. In view of this, genome- and transcriptome-wide identification of WRKY TF family was performed in the C4model plants, Setaria italica (SiWRKY) and S. viridis (SvWRKY), respectively. The study identified 105 SiWRKY and 44 SvWRKY proteins that were computationally analyzed for their physicochemical properties. Sequence alignment and phylogenetic analysis classified these proteins into three major groups, namely I, II, and III with majority of WRKY proteins belonging to group II (53 SiWRKY and 23 SvWRKY), followed by group III (39 SiWRKY and 11 SvWRKY) and group I (10 SiWRKY and 6 SvWRKY). Group II proteins were further classified into 5 subgroups (IIa to IIe) based on their phylogeny. Domain analysis showed the presence of WRKY motif and zinc finger-like structures in these proteins along with additional domains in a few proteins. All SiWRKY genes were physically mapped on the S. italica genome and their duplication analysis revealed that 10 and 8 gene pairs underwent tandem and segmental duplications, respectively. Comparative mapping of SiWRKY and SvWRKY genes in related C4 panicoid genomes demonstrated the orthologous relationships between these genomes. In silico expression analysis of SiWRKY and SvWRKY genes showed their differential expression patterns in different tissues and stress conditions. Expression profiling of candidate SiWRKY genes in response to stress (dehydration and salinity) and hormone treatments (abscisic acid, salicylic acid, and methyl jasmonate) suggested the putative involvement of SiWRKY066 and SiWRKY082 in stress and hormone signaling. These genes could be potential candidates for further characterization to delineate their functional roles in abiotic stress signaling. PMID:26635818

Roles of protein kinase R in cancer: Potential as a therapeutic target.

PubMed

Watanabe, Takao; Imamura, Takeshi; Hiasa, Yoichi

2018-04-01

Double-stranded (ds) RNA-dependent protein kinase (PKR) is a ubiquitously expressed serine/threonine protein kinase. It was initially identified as an innate immune antiviral protein induced by interferon (IFN) and activated by dsRNA. PKR is recognized as a key executor of antiviral host defense. Moreover, it contributes to inflammation and immune regulation through several signaling pathways. In addition to IFN and dsRNA, PKR is activated by multiple stimuli and regulates various signaling pathways including the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-light-chain-enhancer of activated B cells pathways. PKR was initially thought to be a tumor suppressor as a result of its ability to suppress cell growth and interact with major tumor suppressor genes. However, in several types of malignant disease, such as colon and breast cancers, its role remains controversial. In hepatocellular carcinoma, hepatitis C virus (HCV) is the main cause of liver cancer, and PKR inhibits HCV replication, indicating its role as a tumor suppressor. However, PKR is overexpressed in cirrhotic patients, and acts as a tumor promoter through enhancement of cancer cell growth by mediating MAPK or signal transducer and activator of transcription pathways. Moreover, PKR is reportedly required for the activation of inflammasomes and influences metabolic disorders. In the present review, we introduce the multifaceted roles of PKR such as antiviral function, tumor cell growth, regulation of inflammatory immune responses, and maintaining metabolic homeostasis; and discuss future perspectives on PKR biology including its potential as a therapeutic target for liver cancer. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

A Review: Origins of the Dielectric Properties of Proteins and Potential Development as Bio-Sensors

PubMed Central

Bibi, Fabien; Villain, Maud; Guillaume, Carole; Sorli, Brice; Gontard, Nathalie

2016-01-01

Polymers can be classified as synthetic polymers and natural polymers, and are often characterized by their most typical functions namely their high mechanical resistivity, electrical conductivity and dielectric properties. This bibliography report consists in: (i) Defining the origins of the dielectric properties of natural polymers by reviewing proteins. Despite their complex molecular chains, proteins present several points of interest, particularly, their charge content conferring their electrical and dielectric properties; (ii) Identifying factors influencing the dielectric properties of protein films. The effects of vapors and gases such as water vapor, oxygen, carbon dioxide, ammonia and ethanol on the dielectric properties are put forward; (iii) Finally, potential development of protein films as bio-sensors coated on electronic devices for detection of environmental changes particularly humidity or carbon dioxide content in relation with dielectric properties variations are discussed. As the study of the dielectric properties implies imposing an electric field to the material, it was necessary to evaluate the impact of frequency on the polymers and subsequently on their structure. Characterization techniques, on the one hand dielectric spectroscopy devoted for the determination of the glass transition temperature among others, and on the other hand other techniques such as infra-red spectroscopy for structure characterization as a function of moisture content for instance are also introduced. PMID:27527179

Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory

PubMed Central

Fowler, Nicholas J.; Blanford, Christopher F.

2017-01-01

Abstract Blue copper proteins, such as azurin, show dramatic changes in Cu2+/Cu+ reduction potential upon mutation over the full physiological range. Hence, they have important functions in electron transfer and oxidation chemistry and have applications in industrial biotechnology. The details of what determines these reduction potential changes upon mutation are still unclear. Moreover, it has been difficult to model and predict the reduction potential of azurin mutants and currently no unique procedure or workflow pattern exists. Furthermore, high‐level computational methods can be accurate but are too time consuming for practical use. In this work, a novel approach for calculating reduction potentials of azurin mutants is shown, based on a combination of continuum electrostatics, density functional theory and empirical hydrophobicity factors. Our method accurately reproduces experimental reduction potential changes of 30 mutants with respect to wildtype within experimental error and highlights the factors contributing to the reduction potential change. Finally, reduction potentials are predicted for a series of 124 new mutants that have not yet been investigated experimentally. Several mutants are identified that are located well over 10 Å from the copper center that change the reduction potential by more than 85 mV. The work shows that secondary coordination sphere mutations mostly lead to long‐range electrostatic changes and hence can be modeled accurately with continuum electrostatics. PMID:28815759

In Silico Repositioning-Chemogenomics Strategy Identifies New Drugs with Potential Activity against Multiple Life Stages of Schistosoma mansoni

PubMed Central

Neves, Bruno J.; Braga, Rodolpho C.; Bezerra, José C. B.; Cravo, Pedro V. L.; Andrade, Carolina H.

2015-01-01

Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes. PMID:25569258

A proteomic approach to identifying new drug targets (potentiating topoisomerase II poisons).

PubMed

Jenkins, J R

2008-10-01

Topoisomerase II poisons are an established part of best clinical practice for the treatment of a number of solid tumours and haematological malignancies. However, toxicity and resistance to chemotherapeutic drugs often complicate the treatment. Furthermore, topoisomerase II poisons can also induce sister chromatid exchange, chromosomal recombination and chromosome aberrations and are associated with a significant risk of secondary leukaemia. It would therefore be of great clinical benefit if the efficacy of topoisomerase II inhibitors could be enhanced without the increased toxic side effects. It is proposed that clinical agents targeting topoisomerase II can be enhanced by inhibiting proteins that modulate topoisomerase II. The aim is to identify proteins, that by the nature of their interaction with topoisomerase II, represent putative drug targets.

Differential proteomics of human seminal plasma: A potential target for searching male infertility marker proteins.

PubMed

Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita

2012-04-01

The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

DichroMatch at the protein circular dichroism data bank (DM@PCDDB): A web-based tool for identifying protein nearest neighbors using circular dichroism spectroscopy.

PubMed

Whitmore, Lee; Mavridis, Lazaros; Wallace, B A; Janes, Robert W

2018-01-01

Circular dichroism spectroscopy is a well-used, but simple method in structural biology for providing information on the secondary structure and folds of proteins. DichroMatch (DM@PCDDB) is an online tool that is newly available in the Protein Circular Dichroism Data Bank (PCDDB), which takes advantage of the wealth of spectral and metadata deposited therein, to enable identification of spectral nearest neighbors of a query protein based on four different methods of spectral matching. DM@PCDDB can potentially provide novel information about structural relationships between proteins and can be used in comparison studies of protein homologs and orthologs. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

A side-effect free method for identifying cancer drug targets.

PubMed

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

A cysteine-rich plant protein potentiates Potyvirus movement through an interaction with the virus genome-linked protein VPg.

PubMed

Dunoyer, P; Thomas, C; Harrison, S; Revers, F; Maule, A

2004-03-01

We have identified a cellular factor that interacts with the virus genome-linked proteins (VPgs) of a diverse range of potyviruses. The factor, called Potyvirus VPg-interacting protein (PVIP), is a plant-specific protein with homologues in all the species examined, i.e., pea, Arabidopsis thaliana, and Nicotiana benthamiana. The sequence of PVIP does not identify a specific function, although the existence of a "PHD finger" domain may implicate the protein in transcriptional control through chromatin remodeling. Deletion analysis using the yeast two-hybrid system showed that the determinants of the interaction lay close to the N terminus of VPg; indeed, the N-terminal 16 amino acids were shown to be both necessary and sufficient for the interaction with at least one PVIP protein. From a sequence comparison of different potyvirus VPg proteins, a specific amino acid at position 12 was directly implicated in the interaction. This part of VPg is distinct from regions associated with other functional roles of VPg. Through mutation of Turnip mosaic virus (TuMV) at VPg position 12, we showed that the interaction with PVIP affected systemic symptoms in infected plants. This resulted from reduced cell-to-cell and systemic movement more than reduced virus replication, as visualized by comparing green fluorescent protein-tagged wild-type and mutant viruses. Furthermore, by using RNA interference of PVIP in Arabidopsis, we showed that reduced expression of PVIP genes reduced susceptibility to TuMV infection. We conclude that PVIP functions as an ancillary factor to support potyvirus movement in plants.

Identifying Key Proteins in Hg Methylation Pathways of Desulfovibrio by Global Proteomics, Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Summers, Anne O.; Miller, Susan M.; Wall, Judy

2016-06-18

Elemental mercury, Hg(0) is a contaminant at many DOE sites, especially at Oak Ridge National Laboratory (ORNL) where the spread of spilled Hg and its effects on microbial populations have been monitored for decades. To explore the microbial interactions with Hg, we have devised a global proteomic approach capable of directly detecting Hg-adducts of proteins. This technique developed in the facultative anaerobe, Escherichia coli, allows us to identify the proteins most vulnerable to acute exposure to organomercurials phenyl- and ethyl-mercury (as surrogates for the highly neurotoxic methyl-Hg) (Polacco, et al, 2011). We have found >300 such proteins in all metabolicmore » functional groups and cellular compartments; most are highly conserved and can serve as markers for acute Hg exposure (Zink, et al. 2016, in preparation). We have also discovered that acute Hg exposure severely disrupts thiol, iron and redox homeostases, and electrolyte balance (LaVoie, et al., 2015) Thus, we proposed to bring these techniques to bear on the central problem of identifying the cellular proteins involved in bacterial uptake and methylation of mercury and its release from the cell.« less

Potential of protein kinase inhibitors for treating herpesvirus associated disease

PubMed Central

Li, Renfeng; Hayward, S. Diane

2013-01-01

Herpesviruses are ubiquitous human pathogens that establish life-long persistent infections. Clinical manifestations range from mild self-limiting outbreaks such as childhood rashes and cold sores to the more severe and life threatening outcomes of disseminated infection, encephalitis and cancer. Nucleoside analog drugs that target viral DNA replication provide the primary means of treatment. However, extended use of these drugs can result in selection for drug resistant strains, particularly in immunocompromised patients. In this review, we will present recent observations about the participation of cellular protein kinases in herpesvirus biology and discuss the potential for targeting these protein kinases as well as the herpesvirus encoded protein kinases as an anti-herpesvirus therapeutic strategy. PMID:23608036

The antibacterial protein lysozyme identified as the termite egg recognition pheromone.

PubMed

Matsuura, Kenji; Tamura, Takashi; Kobayashi, Norimasa; Yashiro, Toshihisa; Tatsumi, Shingo

2007-08-29

Social insects rely heavily on pheromone communication to maintain their sociality. Egg protection is one of the most fundamental social behaviours in social insects. The recent discovery of the termite-egg mimicking fungus 'termite-ball' and subsequent studies on termite egg protection behaviour have shown that termites can be manipulated by using the termite egg recognition pheromone (TERP), which strongly evokes the egg-carrying and -grooming behaviours of workers. Despite the great scientific and economic importance, TERP has not been identified because of practical difficulties. Herein we identified the antibacterial protein lysozyme as the TERP. We isolated the target protein using ion-exchange and hydrophobic interaction chromatography, and the MALDI-TOF MS analysis showed a molecular size of 14.5 kDa. We found that the TERP provided antibacterial activity against a gram-positive bacterium. Among the currently known antimicrobial proteins, the molecular size of 14.5 kDa limits the target to lysozyme. Termite lysozymes obtained from eggs and salivary glands, and even hen egg lysozyme, showed a strong termite egg recognition activity. Besides eggs themselves, workers also supply lysozyme to eggs through frequent egg-grooming, by which egg surfaces are coated with saliva containing lysozyme. Reverse transcript PCR analysis showed that mRNA of termite lysozyme was expressed in both salivary glands and eggs. Western blot analysis confirmed that lysozyme production begins in immature eggs in queen ovaries. This is the first identification of proteinaceous pheromone in social insects. Researchers have focused almost exclusively on hydrocarbons when searching for recognition pheromones in social insects. The present finding of a proteinaceous pheromone represents a major step forward in, and result in the broadening of, the search for recognition pheromones. This novel function of lysozyme as a termite pheromone illuminates the profound influence of pathogenic

The Antibacterial Protein Lysozyme Identified as the Termite Egg Recognition Pheromone

PubMed Central

Matsuura, Kenji; Tamura, Takashi; Kobayashi, Norimasa; Yashiro, Toshihisa; Tatsumi, Shingo

2007-01-01

Social insects rely heavily on pheromone communication to maintain their sociality. Egg protection is one of the most fundamental social behaviours in social insects. The recent discovery of the termite-egg mimicking fungus ‘termite-ball’ and subsequent studies on termite egg protection behaviour have shown that termites can be manipulated by using the termite egg recognition pheromone (TERP), which strongly evokes the egg-carrying and -grooming behaviours of workers. Despite the great scientific and economic importance, TERP has not been identified because of practical difficulties. Herein we identified the antibacterial protein lysozyme as the TERP. We isolated the target protein using ion-exchange and hydrophobic interaction chromatography, and the MALDI-TOF MS analysis showed a molecular size of 14.5 kDa. We found that the TERP provided antibacterial activity against a gram-positive bacterium. Among the currently known antimicrobial proteins, the molecular size of 14.5 kDa limits the target to lysozyme. Termite lysozymes obtained from eggs and salivary glands, and even hen egg lysozyme, showed a strong termite egg recognition activity. Besides eggs themselves, workers also supply lysozyme to eggs through frequent egg-grooming, by which egg surfaces are coated with saliva containing lysozyme. Reverse transcript PCR analysis showed that mRNA of termite lysozyme was expressed in both salivary glands and eggs. Western blot analysis confirmed that lysozyme production begins in immature eggs in queen ovaries. This is the first identification of proteinaceous pheromone in social insects. Researchers have focused almost exclusively on hydrocarbons when searching for recognition pheromones in social insects. The present finding of a proteinaceous pheromone represents a major step forward in, and result in the broadening of, the search for recognition pheromones. This novel function of lysozyme as a termite pheromone illuminates the profound influence of pathogenic

Beta Atomic Contacts: Identifying Critical Specific Contacts in Protein Binding Interfaces

PubMed Central

Liu, Qian; Kwoh, Chee Keong; Hoi, Steven C. H.

2013-01-01

Specific binding between proteins plays a crucial role in molecular functions and biological processes. Protein binding interfaces and their atomic contacts are typically defined by simple criteria, such as distance-based definitions that only use some threshold of spatial distance in previous studies. These definitions neglect the nearby atomic organization of contact atoms, and thus detect predominant contacts which are interrupted by other atoms. It is questionable whether such kinds of interrupted contacts are as important as other contacts in protein binding. To tackle this challenge, we propose a new definition called beta (β) atomic contacts. Our definition, founded on the β-skeletons in computational geometry, requires that there is no other atom in the contact spheres defined by two contact atoms; this sphere is similar to the van der Waals spheres of atoms. The statistical analysis on a large dataset shows that β contacts are only a small fraction of conventional distance-based contacts. To empirically quantify the importance of β contacts, we design βACV, an SVM classifier with β contacts as input, to classify homodimers from crystal packing. We found that our βACV is able to achieve the state-of-the-art classification performance superior to SVM classifiers with distance-based contacts as input. Our βACV also outperforms several existing methods when being evaluated on several datasets in previous works. The promising empirical performance suggests that β contacts can truly identify critical specific contacts in protein binding interfaces. β contacts thus provide a new model for more precise description of atomic organization in protein quaternary structures than distance-based contacts. PMID:23630569

Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

PubMed

DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High confidence proteomic analysis of yeast LDs identifies additional droplet proteins and reveals connections to dolichol synthesis and sterol acetylation.

PubMed

Currie, Erin; Guo, Xiuling; Christiano, Romain; Chitraju, Chandramohan; Kory, Nora; Harrison, Kenneth; Haas, Joel; Walther, Tobias C; Farese, Robert V

2014-07-01

Accurate protein inventories are essential for understanding an organelle's functions. The lipid droplet (LD) is a ubiquitous intracellular organelle with major functions in lipid storage and metabolism. LDs differ from other organelles because they are bounded by a surface monolayer, presenting unique features for protein targeting to LDs. Many proteins of varied functions have been found in purified LD fractions by proteomics. While these studies have become increasingly sensitive, it is often unclear which of the identified proteins are specific to LDs. Here we used protein correlation profiling to identify 35 proteins that specifically enrich with LD fractions of Saccharomyces cerevisiae Of these candidates, 30 fluorophore-tagged proteins localize to LDs by microscopy, including six proteins, several with human orthologs linked to diseases, which we newly identify as LD proteins (Cab5, Rer2, Say1, Tsc10, YKL047W, and YPR147C). Two of these proteins, Say1, a sterol deacetylase, and Rer2, a cis-isoprenyl transferase, are enzymes involved in sterol and polyprenol metabolism, respectively, and we show their activities are present in LD fractions. Our results provide a highly specific list of yeast LD proteins and reveal that the vast majority of these proteins are involved in lipid metabolism. Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.

Characteristic motifs for families of allergenic proteins

PubMed Central

Ivanciuc, Ovidiu; Garcia, Tzintzuni; Torres, Miguel; Schein, Catherine H.; Braun, Werner

2008-01-01

The identification of potential allergenic proteins is usually done by scanning a database of allergenic proteins and locating known allergens with a high sequence similarity. However, there is no universally accepted cut-off value for sequence similarity to indicate potential IgE cross-reactivity. Further, overall sequence similarity may be less important than discrete areas of similarity in proteins with homologous structure. To identify such areas, we first classified all allergens and their subdomains in the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to their closest protein families as defined in Pfam, and identified conserved physicochemical property motifs characteristic of each group of sequences. Allergens populate only a small subset of all known Pfam families, as all allergenic proteins in SDAP could be grouped to only 130 (of 9318 total) Pfams, and 31 families contain more than four allergens. Conserved physicochemical property motifs for the aligned sequences of the most populated Pfam families were identified with the PCPMer program suite and catalogued in the webserver Motif-Mate (http://born.utmb.edu/motifmate/summary.php). We also determined specific motifs for allergenic members of a family that could distinguish them from non-allergenic ones. These allergen specific motifs should be most useful in database searches for potential allergens. We found that sequence motifs unique to the allergens in three families (seed storage proteins, Bet v 1, and tropomyosin) overlap with known IgE epitopes, thus providing evidence that our motif based approach can be used to assess the potential allergenicity of novel proteins. PMID:18951633

Identifying mRNA sequence elements for target recognition by human Argonaute proteins

PubMed Central

Li, Jingjing; Kim, TaeHyung; Nutiu, Razvan; Ray, Debashish; Hughes, Timothy R.; Zhang, Zhaolei

2014-01-01

It is commonly known that mammalian microRNAs (miRNAs) guide the RNA-induced silencing complex (RISC) to target mRNAs through the seed-pairing rule. However, recent experiments that coimmunoprecipitate the Argonaute proteins (AGOs), the central catalytic component of RISC, have consistently revealed extensive AGO-associated mRNAs that lack seed complementarity with miRNAs. We herein test the hypothesis that AGO has its own binding preference within target mRNAs, independent of guide miRNAs. By systematically analyzing the data from in vivo cross-linking experiments with human AGOs, we have identified a structurally accessible and evolutionarily conserved region (∼10 nucleotides in length) that alone can accurately predict AGO–mRNA associations, independent of the presence of miRNA binding sites. Within this region, we further identified an enriched motif that was replicable on independent AGO-immunoprecipitation data sets. We used RNAcompete to enumerate the RNA-binding preference of human AGO2 to all possible 7-mer RNA sequences and validated the AGO motif in vitro. These findings reveal a novel function of AGOs as sequence-specific RNA-binding proteins, which may aid miRNAs in recognizing their targets with high specificity. PMID:24663241

A Human Proteome Array Approach to Identifying Key Host Proteins Targeted by Toxoplasma Kinase ROP18*

PubMed Central

Yang, Zhaoshou; Hou, Yongheng; Hao, Taofang; Rho, Hee-Sool; Wan, Jun; Luan, Yizhao; Gao, Xin; Yao, Jianping; Pan, Aihua; Xie, Zhi; Qian, Jiang; Liao, Wanqin; Zhu, Heng; Zhou, Xingwang

2017-01-01

Toxoplasma kinase ROP18 is a key molecule responsible for the virulence of Toxoplasma gondii; however, the mechanisms by which ROP18 exerts parasite virulence via interaction with host proteins remain limited to a small number of identified substrates. To identify a broader array of ROP18 substrates, we successfully purified bioactive mature ROP18 and used it to probe a human proteome array. Sixty eight new putative host targets were identified. Functional annotation analysis suggested that these proteins have a variety of functions, including metabolic process, kinase activity and phosphorylation, cell growth, apoptosis and cell death, and immunity, indicating a pleiotropic role of ROP18 kinase. Among these proteins, four candidates, p53, p38, UBE2N, and Smad1, were further validated. We demonstrated that ROP18 targets p53, p38, UBE2N, and Smad1 for degradation. Importantly, we demonstrated that ROP18 phosphorylates Smad1 Ser-187 to trigger its proteasome-dependent degradation. Further functional characterization of the substrates of ROP18 may enhance understanding of the pathogenesis of Toxoplasma infection and provide new therapeutic targets. Similar strategies could be used to identify novel host targets for other microbial kinases functioning at the pathogen-host interface. PMID:28087594

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

PubMed

Tan, Yen Hock; Huang, He; Kihara, Daisuke

2006-08-15

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

NASA Astrophysics Data System (ADS)

Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

2016-05-01

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory.

PubMed

Niknam, Niloofar; Khakzad, Hamed; Arab, Seyed Shahriar; Naderi-Manesh, Hossein

2016-05-01

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Large protein as a potential target for use in rabies diagnostics.

PubMed

Santos Katz, I S; Dias, M H; Lima, I F; Chaves, L B; Ribeiro, O G; Scheffer, K C; Iwai, L K

Rabies is a zoonotic viral disease that remains a serious threat to public health worldwide. The rabies lyssavirus (RABV) genome encodes five structural proteins, multifunctional and significant for pathogenicity. The large protein (L) presents well-conserved genomic regions, which may be a good alternative to generate informative datasets for development of new methods for rabies diagnosis. This paper describes the development of a technique for the identification of L protein in several RABV strains from different hosts, demonstrating that MS-based proteomics is a potential method for antigen identification and a good alternative for rabies diagnosis.

Computational Framework for Analysis of Prey–Prey Associations in Interaction Proteomics Identifies Novel Human Protein–Protein Interactions and Networks

PubMed Central

Saha, Sudipto; Dazard, Jean-Eudes; Xu, Hua; Ewing, Rob M.

2013-01-01

Large-scale protein–protein interaction data sets have been generated for several species including yeast and human and have enabled the identification, quantification, and prediction of cellular molecular networks. Affinity purification-mass spectrometry (AP-MS) is the preeminent methodology for large-scale analysis of protein complexes, performed by immunopurifying a specific “bait” protein and its associated “prey” proteins. The analysis and interpretation of AP-MS data sets is, however, not straightforward. In addition, although yeast AP-MS data sets are relatively comprehensive, current human AP-MS data sets only sparsely cover the human interactome. Here we develop a framework for analysis of AP-MS data sets that addresses the issues of noise, missing data, and sparsity of coverage in the context of a current, real world human AP-MS data set. Our goal is to extend and increase the density of the known human interactome by integrating bait–prey and cocomplexed preys (prey–prey associations) into networks. Our framework incorporates a score for each identified protein, as well as elements of signal processing to improve the confidence of identified protein–protein interactions. We identify many protein networks enriched in known biological processes and functions. In addition, we show that integrated bait–prey and prey–prey interactions can be used to refine network topology and extend known protein networks. PMID:22845868

Microarray-based screening of heat shock protein inhibitors.

PubMed

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

Systemic analysis of genome-wide expression profiles identified potential therapeutic targets of demethylation drugs for glioblastoma.

PubMed

Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian

2017-09-05

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.

A protein isolated from human oviductal tissue in vitro secretion, identified as human lactoferrin, interacts with spermatozoa and oocytes and modulates gamete interaction.

PubMed

Zumoffen, C M; Gil, R; Caille, A M; Morente, C; Munuce, M J; Ghersevich, S A

2013-05-01

reaction was assessed with Pisum sativum agglutinin conjugated with rhodamine. The effect of increasing concentrations of LF (0.1-100 µg/ml) on gamete interaction was evaluated by a sperm-ZP binding assay, using human oocytes donated by women undergoing IVF procedures. A protein isolated by the affinity column was identified as human LF. LF was immunolocalized in human oviductal tissue and detected in oviductal fluid and oviduct epithelial cell homogenates. In the latter case, LF expression was highest at the periovulatory phase of the menstrual cycle (P < 0.01). Different LF binding patterns were observed on spermatozoa depending upon capacitation stage and if the acrosome reaction had occurred. Unstained sperm were most prevalent before capacitation, but after incubation for 6 h under capacitating conditions and in acrosome-reacted sperm LF binding was observed, mainly localized in the equatorial segment and post-acrosomal region of the sperm head. LF binding studies on ZP showed homogenous staining. LF caused a dose-dependent significant inhibition of sperm-ZP interaction, and the effect was already significant (P < 0.01) with the lowest LF concentration used. This study has investigated the effect of LF only on human gamete interaction in vitro and thus has some limitations. Further investigations of the potential mechanisms involved in LF action both on gamete function in vitro and in vivo in animal models are needed to confirm the role of this protein in the reproductive process. The present data indicate that human oviductal LF expression is cycle dependent and inhibited gamete interaction in vitro. No previous data were available about potential direct effects of LF on gamete interaction. It could be thought that the protein is involved in the regulation of the reproductive process, perhaps contributing to prevent polyspermy. Thus, further research is needed to clarify the potential role of LF in the regulation of the fertilization process. This study was

Target gene analysis by microarrays and chromatin immunoprecipitation identifies HEY proteins as highly redundant bHLH repressors.

PubMed

Heisig, Julia; Weber, David; Englberger, Eva; Winkler, Anja; Kneitz, Susanne; Sung, Wing-Kin; Wolf, Elmar; Eilers, Martin; Wei, Chia-Lin; Gessler, Manfred

2012-01-01

HEY bHLH transcription factors have been shown to regulate multiple key steps in cardiovascular development. They can be induced by activated NOTCH receptors, but other upstream stimuli mediated by TGFß and BMP receptors may elicit a similar response. While the basic and helix-loop-helix domains exhibit strong similarity, large parts of the proteins are still unique and may serve divergent functions. The striking overlap of cardiac defects in HEY2 and combined HEY1/HEYL knockout mice suggested that all three HEY genes fulfill overlapping function in target cells. We therefore sought to identify target genes for HEY proteins by microarray expression and ChIPseq analyses in HEK293 cells, cardiomyocytes, and murine hearts. HEY proteins were found to modulate expression of their target gene to a rather limited extent, but with striking functional interchangeability between HEY factors. Chromatin immunoprecipitation revealed a much greater number of potential binding sites that again largely overlap between HEY factors. Binding sites are clustered in the proximal promoter region especially of transcriptional regulators or developmental control genes. Multiple lines of evidence suggest that HEY proteins primarily act as direct transcriptional repressors, while gene activation seems to be due to secondary or indirect effects. Mutagenesis of putative DNA binding residues supports the notion of direct DNA binding. While class B E-box sequences (CACGYG) clearly represent preferred target sequences, there must be additional and more loosely defined modes of DNA binding since many of the target promoters that are efficiently bound by HEY proteins do not contain an E-box motif. These data clearly establish the three HEY bHLH factors as highly redundant transcriptional repressors in vitro and in vivo, which explains the combinatorial action observed in different tissues with overlapping expression.

Target Gene Analysis by Microarrays and Chromatin Immunoprecipitation Identifies HEY Proteins as Highly Redundant bHLH Repressors

PubMed Central

Englberger, Eva; Winkler, Anja; Kneitz, Susanne; Sung, Wing-Kin; Wolf, Elmar; Eilers, Martin; Wei, Chia-Lin; Gessler, Manfred

2012-01-01

HEY bHLH transcription factors have been shown to regulate multiple key steps in cardiovascular development. They can be induced by activated NOTCH receptors, but other upstream stimuli mediated by TGFß and BMP receptors may elicit a similar response. While the basic and helix-loop-helix domains exhibit strong similarity, large parts of the proteins are still unique and may serve divergent functions. The striking overlap of cardiac defects in HEY2 and combined HEY1/HEYL knockout mice suggested that all three HEY genes fulfill overlapping function in target cells. We therefore sought to identify target genes for HEY proteins by microarray expression and ChIPseq analyses in HEK293 cells, cardiomyocytes, and murine hearts. HEY proteins were found to modulate expression of their target gene to a rather limited extent, but with striking functional interchangeability between HEY factors. Chromatin immunoprecipitation revealed a much greater number of potential binding sites that again largely overlap between HEY factors. Binding sites are clustered in the proximal promoter region especially of transcriptional regulators or developmental control genes. Multiple lines of evidence suggest that HEY proteins primarily act as direct transcriptional repressors, while gene activation seems to be due to secondary or indirect effects. Mutagenesis of putative DNA binding residues supports the notion of direct DNA binding. While class B E-box sequences (CACGYG) clearly represent preferred target sequences, there must be additional and more loosely defined modes of DNA binding since many of the target promoters that are efficiently bound by HEY proteins do not contain an E-box motif. These data clearly establish the three HEY bHLH factors as highly redundant transcriptional repressors in vitro and in vivo, which explains the combinatorial action observed in different tissues with overlapping expression. PMID:22615585

A cohort of new adhesive proteins identified from transcriptomic analysis of mussel foot glands.

PubMed

DeMartini, Daniel G; Errico, John M; Sjoestroem, Sebastian; Fenster, April; Waite, J Herbert

2017-06-01

The adaptive attachment of marine mussels to a wide range of substrates in a high-energy, saline environment has been explored for decades and is a significant driver of bioinspired wet adhesion research. Mussel attachment relies on a fibrous holdfast known as the byssus, which is made by a specialized appendage called the foot. Multiple adhesive and structural proteins are rapidly synthesized, secreted and moulded by the foot into holdfast threads. About 10 well-characterized proteins, namely the mussel foot proteins (Mfps), the preCols and the thread matrix proteins, are reported as representing the bulk of these structures. To explore how robust this proposition is, we sequenced the transcriptome of the glandular tissues that produce and secrete the various holdfast components using next-generation sequencing methods. Surprisingly, we found around 15 highly expressed genes that have not previously been characterized, but bear key similarities to the previously defined mussel foot proteins, suggesting additional contribution to byssal function. We verified the validity of these transcripts by polymerase chain reaction, cloning and Sanger sequencing as well as confirming their presence as proteins in the byssus. These newly identified proteins greatly expand the palette of mussel holdfast biochemistry and provide new targets for investigation into bioinspired wet adhesion. © 2017 The Author(s).

Motility screen identifies Drosophila IGF-II mRNA-binding protein--zipcode-binding protein acting in oogenesis and synaptogenesis.

PubMed

Boylan, Kristin L M; Mische, Sarah; Li, Mingang; Marqués, Guillermo; Morin, Xavier; Chia, William; Hays, Thomas S

2008-02-01

The localization of specific mRNAs can establish local protein gradients that generate and control the development of cellular asymmetries. While all evidence underscores the importance of the cytoskeleton in the transport and localization of RNAs, we have limited knowledge of how these events are regulated. Using a visual screen for motile proteins in a collection of GFP protein trap lines, we identified the Drosophila IGF-II mRNA-binding protein (Imp), an ortholog of Xenopus Vg1 RNA binding protein and chicken zipcode-binding protein. In Drosophila, Imp is part of a large, RNase-sensitive complex that is enriched in two polarized cell types, the developing oocyte and the neuron. Using time-lapse confocal microscopy, we establish that both dynein and kinesin contribute to the transport of GFP-Imp particles, and that regulation of transport in egg chambers appears to differ from that in neurons. In Drosophila, loss-of-function Imp mutations are zygotic lethal, and mutants die late as pharate adults. Imp has a function in Drosophila oogenesis that is not essential, as well as functions that are essential during embryogenesis and later development. Germline clones of Imp mutations do not block maternal mRNA localization or oocyte development, but overexpression of a specific Imp isoform disrupts dorsal/ventral polarity. We report here that loss-of-function Imp mutations, as well as Imp overexpression, can alter synaptic terminal growth. Our data show that Imp is transported to the neuromuscular junction, where it may modulate the translation of mRNA targets. In oocytes, where Imp function is not essential, we implicate a specific Imp domain in the establishment of dorsoventral polarity.

A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced Data

PubMed Central

Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

2016-01-01

The Golgi Apparatus (GA) is a major collection and dispatch station for numerous proteins destined for secretion, plasma membranes and lysosomes. The dysfunction of GA proteins can result in neurodegenerative diseases. Therefore, accurate identification of protein subGolgi localizations may assist in drug development and understanding the mechanisms of the GA involved in various cellular processes. In this paper, a new computational method is proposed for identifying cis-Golgi proteins from trans-Golgi proteins. Based on the concept of Common Spatial Patterns (CSP), a novel feature extraction technique is developed to extract evolutionary information from protein sequences. To deal with the imbalanced benchmark dataset, the Synthetic Minority Over-sampling Technique (SMOTE) is adopted. A feature selection method called Random Forest-Recursive Feature Elimination (RF-RFE) is employed to search the optimal features from the CSP based features and g-gap dipeptide composition. Based on the optimal features, a Random Forest (RF) module is used to distinguish cis-Golgi proteins from trans-Golgi proteins. Through the jackknife cross-validation, the proposed method achieves a promising performance with a sensitivity of 0.889, a specificity of 0.880, an accuracy of 0.885, and a Matthew’s Correlation Coefficient (MCC) of 0.765, which remarkably outperforms previous methods. Moreover, when tested on a common independent dataset, our method also achieves a significantly improved performance. These results highlight the promising performance of the proposed method to identify Golgi-resident protein types. Furthermore, the CSP based feature extraction method may provide guidelines for protein function predictions. PMID:26861308

Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory.

PubMed

Fowler, Nicholas J; Blanford, Christopher F; Warwicker, Jim; de Visser, Sam P

2017-11-02

Blue copper proteins, such as azurin, show dramatic changes in Cu 2+ /Cu + reduction potential upon mutation over the full physiological range. Hence, they have important functions in electron transfer and oxidation chemistry and have applications in industrial biotechnology. The details of what determines these reduction potential changes upon mutation are still unclear. Moreover, it has been difficult to model and predict the reduction potential of azurin mutants and currently no unique procedure or workflow pattern exists. Furthermore, high-level computational methods can be accurate but are too time consuming for practical use. In this work, a novel approach for calculating reduction potentials of azurin mutants is shown, based on a combination of continuum electrostatics, density functional theory and empirical hydrophobicity factors. Our method accurately reproduces experimental reduction potential changes of 30 mutants with respect to wildtype within experimental error and highlights the factors contributing to the reduction potential change. Finally, reduction potentials are predicted for a series of 124 new mutants that have not yet been investigated experimentally. Several mutants are identified that are located well over 10 Å from the copper center that change the reduction potential by more than 85 mV. The work shows that secondary coordination sphere mutations mostly lead to long-range electrostatic changes and hence can be modeled accurately with continuum electrostatics. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

MyPMFs: a simple tool for creating statistical potentials to assess protein structural models.

PubMed

Postic, Guillaume; Hamelryck, Thomas; Chomilier, Jacques; Stratmann, Dirk

2018-05-29

Evaluating the model quality of protein structures that evolve in environments with particular physicochemical properties requires scoring functions that are adapted to their specific residue compositions and/or structural characteristics. Thus, computational methods developed for structures from the cytosol cannot work properly on membrane or secreted proteins. Here, we present MyPMFs, an easy-to-use tool that allows users to train statistical potentials of mean force (PMFs) on the protein structures of their choice, with all parameters being adjustable. We demonstrate its use by creating an accurate statistical potential for transmembrane protein domains. We also show its usefulness to study the influence of the physical environment on residue interactions within protein structures. Our open-source software is freely available for download at https://github.com/bibip-impmc/mypmfs. Copyright © 2018. Published by Elsevier B.V.

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Poly-Small Ubiquitin-like Modifier (PolySUMO)-binding Proteins Identified through a String Search*

PubMed Central

Sun, Huaiyu; Hunter, Tony

2012-01-01

Polysumoylation is a crucial cellular response to stresses against genomic integrity or proteostasis. Like the small ubiquitin-like modifier (SUMO)-targeted ubiquitin ligase RNF4, proteins with clustered SUMO-interacting motifs (SIMs) can be important signal transducers downstream of polysumoylation. To identify novel polySUMO-binding proteins, we conducted a computational string search with a custom Python script. We found clustered SIMs in another RING domain protein Arkadia/RNF111. Detailed biochemical analysis of the Arkadia SIMs revealed that dominant SIMs in a SIM cluster often contain a pentameric VIDLT ((V/I/L/F/Y)(V/I)DLT) core sequence that is also found in the SIMs in PIAS family E3s and is likely the best-fitted structure for SUMO recognition. This idea led to the identification of additional novel SIM clusters in FLASH/CASP8AP2, C5orf25, and SOBP/JXC1. We suggest that the clustered SIMs in these proteins form distinct SUMO binding domains to recognize diverse forms of protein sumoylation. PMID:23086935

Chagas disease vector blood meal sources identified by protein mass spectrometry

PubMed Central

Keller, Judith I.; Ballif, Bryan A.; St. Clair, Riley M.; Vincent, James J.; Monroy, M. Carlota

2017-01-01

Chagas disease is a complex vector borne parasitic disease involving blood feeding Triatominae (Hemiptera: Reduviidae) insects, also known as kissing bugs, and the vertebrates they feed on. This disease has tremendous impacts on millions of people and is a global health problem. The etiological agent of Chagas disease, Trypanosoma cruzi (Kinetoplastea: Trypanosomatida: Trypanosomatidae), is deposited on the mammalian host in the insect’s feces during a blood meal, and enters the host’s blood stream through mucous membranes or a break in the skin. Identifying the blood meal sources of triatomine vectors is critical in understanding Chagas disease transmission dynamics, can lead to identification of other vertebrates important in the transmission cycle, and aids management decisions. The latter is particularly important as there is little in the way of effective therapeutics for Chagas disease. Several techniques, mostly DNA-based, are available for blood meal identification. However, further methods are needed, particularly when sample conditions lead to low-quality DNA or to assess the risk of human cross-contamination. We demonstrate a proteomics-based approach, using liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify host-specific hemoglobin peptides for blood meal identification in mouse blood control samples and apply LC-MS/MS for the first time to Triatoma dimidiata insect vectors, tracing blood sources to species. In contrast to most proteins, hemoglobin, stabilized by iron, is incredibly stable even being preserved through geologic time. We compared blood stored with and without an anticoagulant and examined field-collected insect specimens stored in suboptimal conditions such as at room temperature for long periods of time. To our knowledge, this is the first study using LC-MS/MS on field-collected arthropod disease vectors to identify blood meal composition, and where blood meal identification was confirmed with more traditional DNA

A potential role for Helicobacter pylori heat shock protein 60 in gastric tumorigenesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Chen-Si; School of Veterinary Medicine, National Taiwan University, Taipei, Taiwan; He, Pei-Juin

2010-02-05

Helicobacter pylori has been found to promote the malignant process leading to gastric cancer. Heat shock protein 60 of H. pylori (HpHSP60) was previously been identified as a potent immunogene. This study investigates the role of HpHSP60 in gastric cancer carcinogenesis. The effect of HpHSP60 on cell proliferation, anti-death activity, angiogenesis and cell migration were explored. The results showed that HpHSP60 enhanced migration by gastric cancer cells and promoted tube formation by umbilical vein endothelial cells (HUVECs); however, HpHSP60 did not increase cell proliferation nor was this protein able to rescue gastric cancer cells from death. Moreover, the results alsomore » indicated HpHSP60 had different effects on AGS gastric cancer cells or THP-1 monocytic cells in terms of their expression of pro-inflammatory cytokines, which are known to be important to cancer development. We propose that HpHSP60 may trigger the initiation of carcinogenesis by inducing pro-inflammatory cytokine release and by promoting angiogenesis and metastasis. Thus, this extracellular pathogen-derived HSP60 is potentially a vigorous virulence factor that can act as a carcinogen during gastric tumorigenesis.« less

Immunoproteomic Analysis To Identify Shiga Toxin-Producing Escherichia coli Outer Membrane Proteins Expressed during Human Infection

PubMed Central

Montero, David; Orellana, Paz; Gutiérrez, Daniela; Araya, Daniela; Salazar, Juan Carlos; Prado, Valeria; Oñate, Ángel; del Canto, Felipe

2014-01-01

Shiga-toxin producing Escherichia coli (STEC) is the etiologic agent of acute diarrhea, dysentery, and hemolytic-uremic syndrome (HUS). There is no approved vaccine for STEC infection in humans, and antibiotic use is contraindicated, as it promotes Shiga toxin production. In order to identify STEC-associated antigens and immunogenic proteins, outer membrane proteins (OMPs) were extracted from STEC O26:H11, O103, O113:H21, and O157:H7 strains, and commensal E. coli strain HS was used as a control. SDS-PAGE, two-dimensional-PAGE analysis, Western blot assays using sera from pediatric HUS patients and controls, and matrix-assisted laser desorption ionization–tandem time of flight analyses were used to identify 12 immunogenic OMPs, some of which were not reactive with control sera. Importantly, seven of these proteins have not been previously reported to be immunogenic in STEC strains. Among these seven proteins, OmpT and Cah displayed IgG and IgA reactivity with sera from HUS patients. Genes encoding these two proteins were present in a majority of STEC strains. Knowledge of the antigens produced during infection of the host and the immune response to those antigens will be important for future vaccine development. PMID:25156722

Protein and Overtraining: Potential Applications for Free-Living Athletes

PubMed Central

Lowery, Lonnie; Forsythe, Cassandra E

2006-01-01

Despite a more than adequate protein intake in the general population, athletes have special needs and situations that bring it to the forefront. Overtraining is one example. Hard-training athletes are different from sedentary persons from the sub-cellular to whole-organism level. Moreover, competitive, "free-living" (less-monitored) athletes often encounter negative energy balance, sub-optimal dietary variety, injuries, endocrine exacerbations and immune depression. These factors, coupled with "two-a-day" practices and in-season demands require that protein not be dismissed as automatically adequate or worse, deleterious to health. When applying research to practice settings, one should consider methodological aspects such as population specificity and control variables such as energy balance. This review will address data pertinent to the topic of athletic protein needs, particularly from a standpoint of overtraining and soft tissue recovery. Research-driven strategies for adjusting nutrition and exercise assessments will be offered for consideration. Potentially helpful nutrition interventions for preventing and treating training complications will also be presented. PMID:18500962

Screening of Potential Inhibitor against Coat Protein of Apple Chlorotic Leaf Spot Virus.

PubMed

Purohit, Rituraj; Kumar, Sachin; Hallan, Vipin

2018-06-01

In this study, we analyzed Coat protein (CP) of Apple chlorotic leaf spot virus (ACLSV), an important latent virus on Apple. Incidence of the virus is upto 60% in various apple cultivars, affecting yield losses of the order of 10-40% (depending upon the cultivar). CP plays an important role as the sole building block of the viral capsid. Homology approach was used to model 193 amino acid sequence of the coat protein. We used various servers such as ConSurf, TargetS, OSML, COACH, COFACTOR for the prediction of active site residues in coat protein. Virtual screening strategy was employed to search potential inhibitors for CP. Top twenty screened molecules considered for drugability, and toxicity analysis and one potential molecule was further analyzed by docking analysis. Here, we reported a potent molecule which could inhibit the formation of viron assembly by targeting the CP protein of virus.

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis.

PubMed

Jiang, Ting-Ting; Shi, Li-Ying; Chen, Jing; Wei, Li-Liang; Li, Meng; Hu, Yu-Ting; Gan, Lin; Liu, Chang-Ming; Tu, Hui-Hui; Li, Zhi-Bin; Yi, Wen-Jing; Li, Ji-Cheng

2018-06-27

This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy. Copyright © 2018. Published by Elsevier Inc.

Discovery Proteomics Identifies a Molecular Link between the Coatomer Protein Complex I and Androgen Receptor-dependent Transcription*

PubMed Central

Hsiao, Jordy J.; Smits, Melinda M.; Ng, Brandon H.; Lee, Jinhee; Wright, Michael E.

2016-01-01

Aberrant androgen receptor (AR)-dependent transcription is a hallmark of human prostate cancers. At the molecular level, ligand-mediated AR activation is coordinated through spatial and temporal protein-protein interactions involving AR-interacting proteins, which we designate the “AR-interactome.” Despite many years of research, the ligand-sensitive protein complexes involved in ligand-mediated AR activation in prostate tumor cells have not been clearly defined. Here, we describe the development, characterization, and utilization of a novel human LNCaP prostate tumor cell line, N-AR, which stably expresses wild-type AR tagged at its N terminus with the streptavidin-binding peptide epitope (streptavidin-binding peptide-tagged wild-type androgen receptor; SBP-AR). A bioanalytical workflow involving streptavidin chromatography and label-free quantitative mass spectrometry was used to identify SBP-AR and associated ligand-sensitive cytosolic proteins/protein complexes linked to AR activation in prostate tumor cells. Functional studies verified that ligand-sensitive proteins identified in the proteomic screen encoded modulators of AR-mediated transcription, suggesting that these novel proteins were putative SBP-AR-interacting proteins in N-AR cells. This was supported by biochemical associations between recombinant SBP-AR and the ligand-sensitive coatomer protein complex I (COPI) retrograde trafficking complex in vitro. Extensive biochemical and molecular experiments showed that the COPI retrograde complex regulates ligand-mediated AR transcriptional activation, which correlated with the mobilization of the Golgi-localized ARA160 coactivator to the nuclear compartment of prostate tumor cells. Collectively, this study provides a bioanalytical strategy to validate the AR-interactome and define novel AR-interacting proteins involved in ligand-mediated AR activation in prostate tumor cells. Moreover, we describe a cellular system to study how compartment-specific AR

Discovering Potential Pathogens among Fungi Identified as Nonsporulating Molds▿

PubMed Central

Pounder, June I.; Simmon, Keith E.; Barton, Claudia A.; Hohmann, Sheri L.; Brandt, Mary E.; Petti, Cathy A.

2007-01-01

Fungal infections are increasing, particularly among immunocompromised hosts, and a rapid diagnosis is essential to initiate antifungal therapy. Often fungi cannot be identified by conventional methods and are classified as nonsporulating molds (NSM).We sequenced internal transcribed spacer regions from 50 cultures of NSM and found 16 potential pathogens that can be associated with clinical disease. In selected clinical settings, identification of NSM could prove valuable and have an immediate impact on patient management. PMID:17135442

Introduction to current and future protein therapeutics: a protein engineering perspective.

PubMed

Carter, Paul J

2011-05-15

Protein therapeutics and its enabling sister discipline, protein engineering, have emerged since the early 1980s. The first protein therapeutics were recombinant versions of natural proteins. Proteins purposefully modified to increase their clinical potential soon followed with enhancements derived from protein or glycoengineering, Fc fusion or conjugation to polyethylene glycol. Antibody-based drugs subsequently arose as the largest and fastest growing class of protein therapeutics. The rationale for developing better protein therapeutics with enhanced efficacy, greater safety, reduced immunogenicity or improved delivery comes from the convergence of clinical, scientific, technological and commercial drivers that have identified unmet needs and provided strategies to address them. Future protein drugs seem likely to be more extensively engineered to improve their performance, e.g., antibodies and Fc fusion proteins with enhanced effector functions or extended half-life. Two old concepts for improving antibodies, namely antibody-drug conjugates and bispecific antibodies, have advanced to the cusp of clinical success. As for newer protein therapeutic platform technologies, several engineered protein scaffolds are in early clinical development and offer differences and some potential advantages over antibodies. Copyright © 2011 Elsevier Inc. All rights reserved.

Introduction to current and future protein therapeutics: A protein engineering perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carter, Paul J., E-mail: pjc@gene.com

2011-05-15

Protein therapeutics and its enabling sister discipline, protein engineering, have emerged since the early 1980s. The first protein therapeutics were recombinant versions of natural proteins. Proteins purposefully modified to increase their clinical potential soon followed with enhancements derived from protein or glycoengineering, Fc fusion or conjugation to polyethylene glycol. Antibody-based drugs subsequently arose as the largest and fastest growing class of protein therapeutics. The rationale for developing better protein therapeutics with enhanced efficacy, greater safety, reduced immunogenicity or improved delivery comes from the convergence of clinical, scientific, technological and commercial drivers that have identified unmet needs and provided strategies tomore » address them. Future protein drugs seem likely to be more extensively engineered to improve their performance, e.g., antibodies and Fc fusion proteins with enhanced effector functions or extended half-life. Two old concepts for improving antibodies, namely antibody-drug conjugates and bispecific antibodies, have advanced to the cusp of clinical success. As for newer protein therapeutic platform technologies, several engineered protein scaffolds are in early clinical development and offer differences and some potential advantages over antibodies.« less