The Omp85 family of proteins is essential for outer membrane biogenesis in mitochondria and bacteria

Integral proteins in the outer membrane of mitochondria control all aspects of organelle biogenesis, being required for protein import, mitochondrial fission, and, in metazoans, mitochondrial aspects of programmed cell death. How these integral proteins are assembled in the outer membrane had been unclear. In bacteria, Omp85 is an essential component of the protein insertion machinery, and we show that members of the Omp85 protein family are also found in eukaryotes ranging from plants to humans. In eukaryotes, Omp85 is present in the mitochondrial outer membrane. The gene encoding Omp85 is essential for cell viability in yeast, and conditional omp85 mutants have defects that arise from compromised insertion of integral proteins like voltage-dependent anion channel (VDAC) and components of the translocase in the outer membrane of mitochondria (TOM) complex into the mitochondrial outer membrane.

Characterisation of proteins in the milk of fur seals

Milk protein composition was investigated throughout the lactation periods of the Australian fur seal (Arctocephalus pusillus doriferus) and Antarctic fur seal (Arctocephalus gazella). The mean protein content of the milk was found to be 10.9% and 10.6% respectively. The concentration of total protein did not change during lactation, although a decline in casein content of the milk in late lactation was apparent. Milk protein concentration during a foraging/suckling cycle of the Antarctic fur seal analysed at the time of arrival on shore, and 24 h and 72 h after arrival was 12.8%, 11.4% and 12.5% respectively. Re-feeding animals at 72 h resulted in a significant increase in milk protein content to 14.9%. Characterisation of milk protein by SDS-PAGE analysis revealed 5 casein and 10 major whey protein bands. Amino-terminal sequencing indicated that the majority of the whey fraction of the milk is β-lactoglobulin (β-LG). The limited amino acid sequence indicated 3 different β-LGs were secreted in the milk. Subsequently, RT-PCR was used to extend the sequence of one of the β-LGs and translation of the 464 bp fragment indicated that it shared 79% sequence identity with feline β-LG II.

Study of Proteinuria: Isolation of Proteins from the Nephrotic Syndrome

One of the most puzzling phenomena of abnormal renal physiology is the occurrence of the nephrotic syndrome. The syndrome has been defined by a collection of clinical and pathological symptoms, but there is no correlation between the clinical and pathological symptoms nor is the etiology of the syndrome known. Proteinuria is probably the most distinguishing feature in the nephrotic syndrome, and there are two possible explanations for its occurrence: (1) the excessive amounts of protein found in nephrotic urine could be due to an increased basement membrane permeability in the glomerulus of the kidney or (2) dysproteinemia. An attempt has been made to evaluate the theory of dysproteinemia in connection with the syndrome. The albumin fractions of nephrotic urine have been studied for their amino acid composition by separating them from the urine by paper electrophoresis, hydrolyzing them, and identifying the amino acids present by two-dimensional chromatography. There seem to be no variations in the qualitative makeup of nephrotic albumin from that of normal albumin, but the literature shows that there are some slight variations in the quantitative amino acid composition of nephrotic albumin compared with normal albumin. More extensive and highly developed experimentation along the lines of protein structure and composition must be done before it can conclusively be stated that dysproteinemia is of importance in the nephrotic syndrome.

Subcellular localisation of proteins in fluorescent microscope images using a random forest

This paper presents a system that employs random forests to formulate a method for subcellular localisation of proteins. A random forest is an ensemble learner that grows classification trees. Each tree produces a classification decision, and an integrated output is calculated. The system classifies the protein-localisation patterns within fluorescent microscope images. 2D images of HeLa cells that include all major classes of subcellular structures, and the associated feature set are used. The performance of the developed system is compared against that of the support vector machine and decision tree approaches. Three experiments are performed to study the influence of the training and test set size on the performance of the examined methods. The calculated classification errors and execution times are presented and discussed. The lowest classification error (2.9%) has been produced by the developed system.

Identification of proteins that interact with the copper transporter ATP7B

In this study proteins were identified that interact with the key liver enzyme, ATP7B that is affected in the copper toxicity disorder Wilson disease. Detailed characterisation of the interaction with glutaredoxin and dynactin subunit p62 contributes significantly towards our understanding of the mechanisms that regulate copper balance in the body.

Industrial biotechnology for the production of proteins/enzymes for a sustainable future

Worldwide emergence of Industrial biotechnology (IB) is providing opportunities to produce enzymes/proteins with variety of industrial/therapeutic applications. In transitioning the Australian economy towards a sustainable future, Federal government identified the development of IB pathway which would ensure increased productivity, enhanced sustainability, health, safety and reduced environmental footprint. The presentation will revolve around specific stories that drives Deakin University newest technology platform which applies biology and fermentation in an integrated way to play a crucial role in developing cost-effective technologies for the development of molecules that can benefit pharmaceutical and food industry in regional Victoria and Australia in general. The talk will also highlight specific examples where new products like recombinant rhamnosidase (an enzyme used for the production of flavonoids with health benefits) and ribosome inactivating proteins (detected in medicinal plants which possess RNA N- glycosidase activity that depurinates the major rRNA, thus damaging ribosome in an irreversible manner and arresting protein synthesis) would be made available through bioprocessing.

Functional analysis of proteins involved in Plasmodium falciparum merozoite invasion of red blood cells

Plasmodium falciparum causes the most lethal form of malaria in humans and is responsible for over two million deaths per year. The development of a vaccine against this parasite is an urgent priority and potential protein targets include those on the surface of the asexual merozoite stage, the form that invades the host erythrocyte. The development of methods to transfect P. falciparum has enabled the construction of gain-of-function and loss-of-function mutants and provided new strategies to analyse the role of parasite proteins. In this review, we describe the use of this technology to examine the role of merozoite antigens in erythrocyte invasion and to address their potential as vaccine candidates.

Dynamically predicting protein functions from semantic associations of proteins

Predicting functions of un-annotated proteins is a significant challenge in the post-genomics era. Among existing computational approaches, exploiting interactions between proteins to predict functions of un-annotated proteins is widely used. However, it remains difficult to extract semantic associations between proteins (i.e. protein associations in terms of protein functionality) from protein interactions and incorporate extracted semantic associations to more effectively predict protein functions. Furthermore, existing approaches and algorithms regard the function prediction as a one-off procedure, ignoring dynamic and mutual associations between proteins. Therefore, deriving and exploiting semantic associations between proteins to dynamically predict functions are a promising and challenging approach for achieving better prediction results. In this paper, we propose an innovative algorithm to incorporate semantic associations between proteins into a dynamic procedure of protein function prediction. The semantic association between two proteins is measured by the semantic similarity of two proteins which is defined by the similarities of functions two proteins possess. To achieve better prediction results, function similarities are also incorporated into the prediction procedure. The algorithm dynamically predicts functions by iteratively selecting functions for the un-annotated protein and updating the similarities between the un-annotated protein and its neighbour annotated proteins until such suitable functions are selected that the similarities no longer change. The experimental results on real protein interaction datasets demonstrated that our method outperformed the similar and non-dynamic function prediction methods. Incorporating semantic associations between proteins into a dynamic procedure of function prediction reflects intrinsic relationships among proteins as well as dynamic features of protein interactions, and therefore, can significantly improve prediction results.

First-principles based force-field for the interaction of proteins with Au(100)(5 x 1): an extension of GolP-CHARMM

Noncovalent recognition between peptides and inorganic materials is an established phenomenon. Key to exploiting these interactions in a wide range of materials self-assembly applications would be to harness the facet-selective control of peptide binding onto these materials. Fundamental understanding of what drives facet-selectivity in peptide binding is developing, but as yet is not sufficient to enable design of predictable facet-specific sequences. Computational simulation of the aqueous peptide-gold interface, commonly used to understand the mechanisms driving adsorption at an atomic level, has thus far neglected the role that surface reconstruction might play in facet specificity. Here the polarizable GolP-CHARMM suite of force fields is extended to include the reconstructed Au(100) surface. The force field, compatible with the bio-organic force field CHARMM, is parametrized using first-principles data. Our extended force field is tailored to reproduce the heterogeneity of weak chemisorbing N and S species to specific locations in the Au(100)(5 × 1) surface identified from the first-principles calculations. We apply our new model to predict and compare the three-dimensional structure of liquid water at Au(111), Au(100)(1 × 1), and Au(100)(5 × 1) interfaces. Using molecular dynamics simulations, we predict an increased likelihood for water-mediated peptide adsorption at the aqueous-Au(100)(1 × 1) interface compared with the Au(100)(5 × 1) interface. Therefore, our findings suggest that peptide binding can discriminate between the native and reconstructed Au(100) interfaces and that the role of reconstruction on binding at the Au(100) interface should not be neglected. © 2013 American Chemical Society.

Structural classification of proteins through amino acid sequence using interval type-2 fuzzy logic system

This paper introduces a new multi-output interval type-2 fuzzy logic system (MOIT2FLS) that is automatically constructed from unsupervised data clustering method and trained using heuristic genetic algorithm for a protein secondary structure classification. Three structure classes are distinguished including helix, strand (sheet) and coil which correspond to three outputs of the MOIT2FLS. Quantitative properties of amino acids are used to characterize the twenty amino acids rather than the widely used computationally expensive binary encoding scheme. Amino acid sequences are parsed into learnable patterns using a local moving window strategy. Three clustering tasks are performed using the adaptive vector quantization method to derive an equal number of initial rules for each type of secondary structure. Genetic algorithm is applied to optimally adjust parameters of the MOIT2FLS with the purpose of maximizing the Q3 measure. Comprehensive experimental results demonstrate the strong superiority of the proposed approach over the traditional methods including Chou-Fasman method, Garnier-Osguthorpe-Robson method, and artificial neural network models.

Parametric investigation of batch adsorption of proteins onto polymeric particles

Background: Effective bimolecular adsorption of proteins onto solid matrices is characterized by in-depth understanding of the biophysical features essential to optimize the adsorption performance. Results: The adsorption of bovine serum albumin (BSA) onto anion-exchange Q-sepharose solid particulate support was investigated in batch adsorption experiments. Adsorption kinetics and isotherms were developed as a function of key industrially relevant parameters such as polymer loading, stirring speed, buffer pH, protein concentration and the state of protein dispersion (solid/aqueous) in order to optimize binding performance and adsorption capacity. Experimental results showed that the first order rate constant is higher at higher stirring speed, higher polymer loading, and under alkaline conditions, with a corresponding increase in equilibrium adsorption capacity. Increasing the stirring speed and using aqueous dispersion protein system increased the adsorption rate, but the maximum protein adsorption was unaffected. Regardless of the stirring speed, the adsorption capacity of the polymer was 2.8 mg/ml. However, doubling the polymer loading increased the adsorption capacity to 9.4 mg/ml. Conclusions: The result demonstrates that there exists a minimum amount of polymer loading required to achieve maximum protein adsorption capacity under specific process conditions.

Partial characterization of proteins from baru (Dipteryx alata Vog) seeds

BACKGROUND: Baru (Dipteryx alata Vog.) is a fruit distributed throughout the Brazilian savanna and contains a seed with a high protein content, whose properties have been rarely explored. The purpose of this study was to characterize this protein, especially by isolation and quantifying its fractions and measuring some of its molecular properties.RESULTS: Baru seeds contain 244 g kg(-1) protein on a dry weight basis. Solubility profiles showed a preponderance of globulins. This fraction dominated the seed composition, with 61.7 wt% of the total soluble proteins. Albumins and glutelins accounted for 14 and 3.3 wt%, respectively. SDS-PAGE resolution of albumin and globulin showed main bands with molecular weights of 84 kDa and 64,66 and 73 kDa, respectively. The total protein of the flour and the globulin showed values of in vitro digestibility of 85.59% and 90.54%, relative to casein. Total globulin produced only one chromatographic peak, both on Sepharose CL-6B gel filtration and on DEAE-cellulose ion-exchange columns, eluted at a concentration of 0.12 mol L(-1) NaCl.CONCLUSION: The baru seed had high protein content with large quantities of storage proteins. The chromatographic and solubility profiles indicate the predominance of a fraction with characteristics of a legumin-type protein. (C) 2011 Society of Chemical Industry