A proteome map of primary cultured rat Schwann cells

Background

Schwann cells (SCs) are the principal glial cells of the peripheral nervous system with a wide range of biological functions. SCs play a key role in peripheral nerve regeneration and are involved in several hereditary peripheral neuropathies. The objective of this study was to gain new insight into the whole protein composition of SCs.

Results

Two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D LC-MS/MS) was performed to identify the protein expressions in primary cultured SCs of rats. We identified a total of 1,232 proteins, which were categorized into 20 functional classes. We also used quantitative real time RT-PCR and Western blot analysis to validate some of proteomics-identified proteins.

Conclusion

We showed for the first time the proteome map of SCs. Our data could serve as a reference library to provide basic information for understanding SC biology.     

Towards defining the nuclear proteome

Background

The nucleus is a complex cellular organelle and accurately defining its protein content is essential before any systematic characterization can be considered.

Results

We report direct evidence for 2,568 mammalian proteins within the nuclear proteome: the nuclear subcellular localization of 1,529 proteins based on a high-throughput subcellular localization protocol of full-length proteins and an additional 1,039 proteins for which clear experimental evidence is documented in published literature. This is direct evidence that the nuclear proteome consists of at least 14% of the entire proteome. This dataset was used to evaluate computational approaches designed to identify additional nuclear proteins.

Conclusion

This represents direct experimental evidence that the nuclear proteome consists of at least 14% of the entire proteome. This high-quality nuclear proteome dataset was used to evaluate computational approaches designed to identify additional nuclear proteins. Based on this analysis, researchers can determine the stringency and types of lines of evidence they consider to infer the size and complement of the nuclear proteome.     

GTOP: a database of protein structures predicted from genome sequences

Large-scale genome projects generate an unprecedented number of protein sequences, most of them are experimentally uncharacterized. Predicting the 3D structures of sequences provides important clues as to their functions. We constructed the Genomes TO Protein structures and functions (GTOP) database, containing protein fold predictions of a huge number of sequences. Predictions are mainly carried out with the homology search program PSI-BLAST, currently the most popular among high-sensitivity profile search methods. GTOP also includes the results of other analyses, e.g. homology and motif search, detection of transmembrane helices and repetitive sequences. We have completed analyzing the sequences of 41 organisms, with the number of proteins exceeding 120 000 in total. GTOP uses a graphical viewer to present the analytical results of each ORF in one page in a ‘color-bar’ format. The assigned 3D structures are presented by Chime plug-in or RasMol. The binding sites of ligands are also included, providing functional information. The GTOP server is available at http://spock.genes.nig.ac.jp/~genome/gtop.html.     

REFOLDdb: a new and sustainable gateway to experimental protocols for protein refolding

Background

More than 7000 papers related to “protein refolding” have been published to date, with approximately 300 reports each year during the last decade. Whilst some of these papers provide experimental protocols for protein refolding, a survey in the structural life science communities showed a necessity for a comprehensive database for refolding techniques. We therefore have developed a new resource – “REFOLDdb” that collects refolding techniques into a single, searchable repository to help researchers develop refolding protocols for proteins of interest.

Results

We based our resource on the existing REFOLD database, which has not been updated since 2009. We redesigned the data format to be more concise, allowing consistent representations among data entries compared with the original REFOLD database. The remodeled data architecture enhances the search efficiency and improves the sustainability of the database. After an exhaustive literature search we added experimental refolding protocols from reports published 2009 to early 2017. In addition to this new data, we fully converted and integrated existing REFOLD data into our new resource. REFOLDdb contains 1877 entries as of March 17^th, 2017, and is freely available at http://p4d-info.nig.ac.jp/refolddb/.

Conclusion

REFOLDdb is a unique database for the life sciences research community, providing annotated information for designing new refolding protocols and customizing existing methodologies. We envisage that this resource will find wide utility across broad disciplines that rely on the production of pure, active, recombinant proteins. Furthermore, the database also provides a useful overview of the recent trends and statistics in refolding technology development.

     

Characterization of the Human Cervical Mucous Proteome

Introduction

Cervical cancer is among the most common cancers in women worldwide. Discovery of biomarkers for the early detection of cervical cancer would improve current screening practices and reduce the burden of disease.

Objective

In this study, we report characterization of the human cervical mucous proteome as the first step towards protein biomarker discovery.

Methods

The protein composition was characterized using one- and two-dimensional gel electrophoresis, and liquid chromatography coupled with mass spectrometry. We chose to use this combination of traditional biochemical techniques and proteomics to allow a more comprehensive analysis.

Results and Conclusion

A total of 107 unique proteins were identified, with plasma proteins being most abundant. These proteins represented the major functional categories of metabolism, immune response, and cellular transport. Removal of high molecular weight abundant proteins by immunoaffinity purification did not significantly increase the number of protein spots resolved. We also analyzed phosphorylated and glycosylated proteins by fluorescent post-staining procedures. The profiling of cervical mucous proteins and their post-translational modifications can be used to further our understanding of the cervical mucous proteome.     

Crystal structural analysis of human serum albumin complexed with hemin and fatty acid

Background

Human serum albumin (HSA) is an abundant plasma protein that binds a wide variety of hydrophobic ligands including fatty acids, bilirubin, thyroxine and hemin. Although HSA-heme complexes do not bind oxygen reversibly, it may be possible to develop modified HSA proteins or heme groups that will confer this ability on the complex.

Results

We present here the crystal structure of a ternary HSA-hemin-myristate complex, formed at a 1:1:4 molar ratio, that contains a single hemin group bound to subdomain IB and myristate bound at six sites. The complex displays a conformation that is intermediate between defatted HSA and HSA-fatty acid complexes; this is likely to be due to low myristate occupancy in the fatty acid binding sites that drive the conformational change. The hemin group is bound within a narrow D-shaped hydrophobic cavity which usually accommodates fatty acid; the hemin propionate groups are coordinated by a triad of basic residues at the pocket entrance. The iron atom in the centre of the hemin is coordinated by Tyr161.

Conclusion

The structure of the HSA-hemin-myristate complex (PDB ID 1o9x) reveals the key polar and hydrophobic interactions that determine the hemin-binding specificity of HSA. The details of the hemin-binding environment of HSA provide a structural foundation for efforts to modify the protein and/or the heme molecule in order to engineer complexes that have favourable oxygen-binding properties.

     

Identification of three wheat globulin genes by screening a Triticum aestivum BAC genomic library with cDNA from a diabetes-associated globulin

Background

Plant systemic signaling characterized by the long distance transport of molecules across plant organs involves the xylem and phloem conduits. Root-microbe interactions generate systemic signals that are transported to aerial organs via the xylem sap. We analyzed the xylem sap proteome of soybean seedlings in response to pathogenic and symbiotic interactions to identify systemic signaling proteins and other differentially expressed proteins.

Results

We observed the increase of a serine protease and peroxidase in the xylem sap in response to Phytophthora sojae elicitor treatment. The high molecular weight fraction of soybean xylem sap was found to promote the growth of Neurospora crassa in vitro at lower concentrations and inhibit growth at higher concentrations. Sap from soybean plants treated with a P. sojae elicitor had a significantly higher inhibitory effect than sap from control soybean plants. When soybean seedlings were inoculated with the symbiont Bradyrhizobium japonicum, the abundance of a xyloglucan transendoglycosyl transferase protein increased in the xylem sap. However, RNAi-mediated silencing of the corresponding gene did not significantly affect nodulation in soybean hairy root composite plants.

Conclusion

Our study identified a number of sap proteins from soybean that are differentially induced in response to B. japonicum and P. sojae elicitor treatments and a majority of them were secreted proteins.     

Structure of glutathione S-transferase of the filarial parasite Wuchereria bancrofti: a target for drug development against adult worm

A three dimensional structural model of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. The three dimensional X-ray crystal structure of porcine -class GST with PDB ID: 2gsr-A chain protein with 42% sequential and functional homology was used as the template. The model of wbGST built by MODELLER6v2 was analyzed by the PROCHECK programs. Ramachandran plot analysis showed that 93.5% of the residues are in the core region followed by 5.4 and 1.1% residues in the allowed and generously allowed regions, respectively. None of the non-glycine residues is in disallowed regions. The PROSA II z-score and the energy graph for the final model further confirmed the quality of the modeled structure. The computationally modeled three-dimensional (3D) structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668). 1SFM was used for docking with GST inhibitors by Hex4.2 macromolecular docking using spherical polar Fourier correlations.Figure: A three-dimensional (3D) structure of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. This modeled 3D structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668).     

Serum Proteome Pool Changes in Type 2 Diabetic Patients Treated with Anakinra

Introduction

High glucose concentrations induce the production of IL-1β in human pancreatic beta cells leading to impaired insulin secretion, decreased cell proliferation and apoptosis. Blockade of IL-1 signalling with the recombinant human IL-1 receptor antagonist anakinra reduces HbA_1c in patients with type 2 diabetes. The aims of the present study were to identify: (1) candidate surrogates for improved glycemia in type 2 diabetic patients following treatment with anakinra, (2) proteins that change serum concentration because of anakinra treatment and (3) candidate biomarkers that may predict improved glycemia in type 2 diabetic subjects treated with anakinra.

Methods

Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry was used to analyse serum from 67 type 2 diabetic patients who had received either placebo or anakinra for 13 weeks. Immunodepletion with magnetic protein G bead-coupled antibodies were used to identify three proteins and Western blotting confirmed the biomarker concentration pattern of four proteins.

Results

Twelve proteins, including transthyretin (TTR) and transferrin (Tf), were identified as candidate surrogates for improved glycemia. Six proteins, including retinol-binding protein 4 (RPB4) and a protein tentatively identified as modified apolipoprotein-A1 (apo-AI), increased expression as a consequence of anakinra treatment and four proteins were candidate biomarkers that may predict improved glycemia following anakinra treatment. Furthermore, we found increased RBP4 to be associated with improved beta cell secretory function and increased TTR, RBP4 and modified apo-AI (peak at 28,601 Da) to be associated with decreased inflammation.

Conclusions

Anakinra-induced changes in the serum proteome pool associated with a decreased cardiovascular disease risk, reduced inflammation and improved beta cell secretory function.     

Trypsin-induced proteome alteration during cell subculture in mammalian cells

Background

It is essential to subculture the cells once cultured cells reach confluence. For this, trypsin is frequently applied to dissociate adhesive cells from the substratum. However, due to the proteolytic activity of trypsin, cell surface proteins are often cleaved, which leads to dysregulation of the cell functions.

Methods

In this study, a triplicate 2D-DIGE strategy has been performed to monitor trypsin-induced proteome alterations. The differentially expressed spots were identified by MALDI-TOF MS and validated by immunoblotting.

Results

36 proteins are found to be differentially expressed in cells treated with trypsin, and proteins that are known to regulate cell metabolism, growth regulation, mitochondrial electron transportation and cell adhesion are down-regulated and proteins that regulate cell apoptosis are up-regulated after trypsin treatment. Further study shows that bcl-2 is down-regulated, p53 and p21 are both up-regulated after trypsinization.

Conclusions

In summary, this is the first report that uses the proteomic approach to thoroughly study trypsin-induced cell physiological changes and provides researchers in carrying out their experimental design.     

Uncoupling protein 2 G(-866)A polymorphism: a new gene polymorphism associated with C-reactive protein in type 2 diabetic patients C-reactive protein in type 2 diabetic patients

Objective

To evaluate glycemic variability associated with two different premixed insulin analogue formulations when used in a twice-daily regimen.

Patients and Methods

Subjects comprised type 2 diabetic patients aged 20-79 years, treated with twice daily premixed insulin or insulin analogue formulations. All subjects were hospitalized for 6 days and randomized to receive either Humalog Mix 25 (Mix 25) or Humalog Mix 50 (Mix 50). They were then crossed over to the other arm between day 3 and day 4 of the study. Continuous glucose monitoring (CGM) was performed on all subjects to examine the differences in glycemic variability.

Results

Eleven type 2 diabetic patients were enrolled. No significant difference was found in 24-hour mean glucose values and their SDs, pre-meal glucose values, increases from pre-meal to peak glucose values, or time to peak glucose levels between either group. However, the mean glucose values observed during 0-8 hrs were significantly lower with Mix 25 compared to Mix 50 (128 vs. 147 mg/dL; p = 0.024).

Conclusions

The twice-daily Mix 25 regimen provided superior overnight glycemic control compared to the Mix 50 regimen in Japanese patients with type 2 diabetes. However, both twice-daily regimens with either Mix 25 or Mix 50 provided inadequate post-lunch glycemic control.

Trial Registration

Current Controlled Trials UMIN000001327     

An interactomics overview of the human and bovine milk proteome over lactation

Background

Milk is the most important food for growth and development of the neonate, because of its nutrient composition and presence of many bioactive proteins. Differences between human and bovine milk in low abundant proteins have not been extensively studied. To better understand the differences between human and bovine milk, the qualitative and quantitative differences in the milk proteome as well as their changes over lactation were compared using both label-free and labelled proteomics techniques. These datasets were analysed and compared, to better understand the role of milk proteins in development of the newborn.

Methods

Human and bovine milk samples were prepared by using filter-aided sample preparation (FASP) combined with dimethyl labelling and analysed by nano LC LTQ-Orbitrap XL mass spectrometry.

Results

The human and bovine milk proteome show similarities with regard to the distribution over biological functions, especially the dominant presence of enzymes, transport and immune-related proteins. At a quantitative level, the human and bovine milk proteome differed not only between species but also over lactation within species. Dominant enzymes that differed between species were those assisting in nutrient digestion, with bile salt-activated lipase being abundant in human milk and pancreatic ribonuclease being abundant in bovine milk. As lactation advances, immune-related proteins decreased slower in human milk compared to bovine milk. Notwithstanding these quantitative differences, analysis of human and bovine co-expression networks and protein-protein interaction networks indicated that a subset of milk proteins displayed highly similar interactions in each of the different networks, which may be related to the general importance of milk in nutrition and healthy development of the newborn.

Conclusions

Our findings promote a better understanding of the differences and similarities in dynamics of human and bovine milk proteins, thereby also providing guidance for further improvement of infant formula.

     

MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments

Background

Protein-protein interaction (PPI) plays a core role in cellular functions. Massively parallel supercomputing systems have been actively developed over the past few years, which enable large-scale biological problems to be solved, such as PPI network prediction based on tertiary structures.

Results

We have developed a high throughput and ultra-fast PPI prediction system based on rigid docking, “MEGADOCK”, by employing a hybrid parallelization (MPI/OpenMP) technique assuming usages on massively parallel supercomputing systems. MEGADOCK displays significantly faster processing speed in the rigid-body docking process that leads to full utilization of protein tertiary structural data for large-scale and network-level problems in systems biology. Moreover, the system was scalable as shown by measurements carried out on two supercomputing environments. We then conducted prediction of biological PPI networks using the post-docking analysis.

Conclusions

We present a new protein-protein docking engine aimed at exhaustive docking of mega-order numbers of protein pairs. The system was shown to be scalable by running on thousands of nodes. The software package is available at: http://www.bi.cs.titech.ac.jp/megadock/k/.

     

The extracellular proteome of Rhizobium etli CE3 in exponential and stationary growth phase

Background

The extracellular proteome or secretome of symbiotic bacteria like Rhizobium etli is presumed to be a key element of their infection strategy and survival. Rhizobia infect the roots of leguminous plants and establish a mutually beneficial symbiosis. To find out the possible role of secreted proteins we analyzed the extracellular proteome of R. etli CE3 in the exponential and stationary growth phases in minimal medium, supplemented with succinate-ammonium.

Results

The extracellular proteins were obtained by phenol extraction and identified by LC-ESI MS/MS. We identified 192 and 191 proteins for the exponential and stationary phases respectively. Using the software Signal P, we predicted signal peptides for 12.95% and 35.60% of the proteins identified in the exponential and stationary phases, respectively, which could therefore be secreted by the Sec pathway. For the exponential growth phase, we found in abundance proteins like the ribosomal proteins, toxins and proteins belonging to the group "defence mechanisms". For the stationary growth phase, we found that the most abundant proteins were those with unknown function, and in many of these we identified characteristic domains of proteases and peptidases.

Conclusions

Our study provided the first dataset of the secretome of R. etli and its modifications, which may lead to novel insights into the adaptive response of different stages of growth. In addition, we found a high number of proteins with unknown function; these proteins could be analyzed in future research to elucidate their role in the extracellular proteome of R. etli.     

Protein Functional Surfaces: Global Shape Matching and Local Spatial Alignments of Ligand Binding Sites

Background

Protein surfaces comprise only a fraction of the total residues but are the most conserved functional features of proteins. Surfaces performing identical functions are found in proteins absent of any sequence or fold similarity. While biochemical activity can be attributed to a few key residues, the broader surrounding environment plays an equally important role.

Results

We describe a methodology that attempts to optimize two components, global shape and local physicochemical texture, for evaluating the similarity between a pair of surfaces. Surface shape similarity is assessed using a three-dimensional object recognition algorithm and physicochemical texture similarity is assessed through a spatial alignment of conserved residues between the surfaces. The comparisons are used in tandem to efficiently search the Global Protein Surface Survey (GPSS), a library of annotated surfaces derived from structures in the PDB, for studying evolutionary relationships and uncovering novel similarities between proteins.

Conclusion

We provide an assessment of our method using library retrieval experiments for identifying functionally homologous surfaces binding different ligands, functionally diverse surfaces binding the same ligand, and binding surfaces of ubiquitous and conformationally flexible ligands. Results using surface similarity to predict function for proteins of unknown function are reported. Additionally, an automated analysis of the ATP binding surface landscape is presented to provide insight into the correlation between surface similarity and function for structures in the PDB and for the subset of protein kinases.     

New Knowledge from Old: In silico discovery of novel protein domains in Streptomyces coelicolor

Background

Streptomyces coelicolor has long been considered a remarkable bacterium with a complex life-cycle, ubiquitous environmental distribution, linear chromosomes and plasmids, and a huge range of pharmaceutically useful secondary metabolites. Completion of the genome sequence demonstrated that this diversity carried through to the genetic level, with over 7000 genes identified. We sought to expand our understanding of this organism at the molecular level through identification and annotation of novel protein domains. Protein domains are the evolutionary conserved units from which proteins are formed.

Results

Two automated methods were employed to rapidly generate an optimised set of targets, which were subsequently analysed manually. A final set of 37 domains or structural repeats, represented 204 times in the genome, was developed. Using these families enabled us to correlate items of information from many different resources. Several immediately enhance our understanding both of S. coelicolor and also general bacterial molecular mechanisms, including cell wall biosynthesis regulation and streptomycete telomere maintenance.

Discussion

Delineation of protein domain families enables detailed analysis of protein function, as well as identification of likely regions or residues of particular interest. Hence this kind of prior approach can increase the rate of discovery in the laboratory. Furthermore we demonstrate that using this type of in silico method it is possible to fairly rapidly generate new biological information from previously uncorrelated data.