The MultiBac Protein Complex Production Platform at the EMBL

Proteomics research revealed the impressive complexity of eukaryotic proteomes in unprecedented detail. It is now a commonly accepted notion that proteins in cells mostly exist not as isolated entities but exert their biological activity in association with many other proteins, in humans ten or more, forming assembly lines in the cell for most if not all vital functions.^1,2 Knowledge of the function and architecture of these multiprotein assemblies requires their provision in superior quality and sufficient quantity for detailed analysis. The paucity of many protein complexes in cells, in particular in eukaryotes, prohibits their extraction from native sources, and necessitates recombinant production. The baculovirus expression vector system (BEVS) has proven to be particularly useful for producing eukaryotic proteins, the activity of which often relies on post-translational processing that other commonly used expression systems often cannot support.³ BEVS use a recombinant baculovirus into which the gene of interest was inserted to infect insect cell cultures which in turn produce the protein of choice. MultiBac is a BEVS that has been particularly tailored for the production of eukaryotic protein complexes that contain many subunits.⁴ A vital prerequisite for efficient production of proteins and their complexes are robust protocols for all steps involved in an expression experiment that ideally can be implemented as standard operating procedures (SOPs) and followed also by non-specialist users with comparative ease. The MultiBac platform at the European Molecular Biology Laboratory (EMBL) uses SOPs for all steps involved in a multiprotein complex expression experiment, starting from insertion of the genes into an engineered baculoviral genome optimized for heterologous protein production properties to small-scale analysis of the protein specimens produced.^5-8 The platform is installed in an open-access mode at EMBL Grenoble and has supported many scientists from academia and industry to accelerate protein complex research projects.     

Phytochemical Diversity of Murraya koenigii (L.) Spreng. from Western Himalaya

Murraya koenigii (L.) Spreng. (Rutaceae), commonly known as ‘curry leaf tree’, is a popular spice and condiment of India. To explore the diversity of the essential‐oil yield and aroma profile of curry leaf, growing wild in foot and mid hills of north India, 58 populations were collected during spring season. M. koenigii populations were found to grow up to an altitude of 1487 m in north India. Comparative results showed considerable variations in the essential‐oil yield and composition. The essential‐oil yield varied from 0.14 to 0.80% in shade‐dried leaves of different populations of M. koenigii. Analysis of the essential oils by GC and GC/MS, and the subsequent classification by statistical analysis resulted in four clusters with significant variations in their terpenoid composition. Major components of the essential oils of investigated populations were α‐pinene ( 2 ; 4.5–71.5%), sabinene ( 3 ; <0.05–66.1%), (E)‐caryophyllene ( 11 ; 1.6–18.0%), β‐pinene ( 4 ; <0.05–13.6%), terpinen‐4‐ol ( 9 ; 0.0–8.4%), γ‐terpinene ( 8 ; 0.2–7.4%), limonene ( 7 ; 1.1–5.5%), α‐terpinene ( 6 ; 0.0–4.5%), (E)‐nerolidol ( 14 ; 0.0–4.1%), α‐humulene ( 12 ; 0.6–3.5%), α‐thujene ( 1 ; 0.0–2.5%), β‐elemene ( 10 ; 0.2–2.4%), β‐selinene ( 13 ; 0.2–2.3%), and myrcene ( 5 ; 0.5–2.1%). Comparison of the present results with those in earlier reports revealed new chemotypes of M. koenigii in investigated populations from Western Himalaya. The present study documents M. koenigii populations having higher amounts of sabinene ( 3 ; up to 66.1%) for the first time.     

Construction of an amperometric TG biosensor based on AuPPy nanocomposite and poly (indole-5-carboxylic acid) modified Au electrode

A method is described for construction of an amperometric triglyceride (TG) biosensor based on covalent co-immobilization of lipase, glycerol kinase and glycerol-3-phosphate oxidase onto gold polypyrrole nanocomposite decorated poly indole-5-carboxylic acid electrodeposited on the surface of a gold electrode. The enzyme electrode was characterized by transmission electron microscopy, scanning electron microscopy, electrochemical impedance studies, Fourier transform infrared spectroscopy and cyclic voltammetry. Biosensor showed optimum response within 4 s at pH 6.5 and 35 °C, when polarized at +0.1 V against Ag/AgCl. There was a linear relationship between sensor response and triolein concentration in the range 50–700 mg/dl. Biosensor was employed for determination of TG in serum. Detection limit of the biosensor was 20 mg/dl. Biosensor was evaluated with 91–95 % recovery of added triolein in sera and 4.14 and 5.85 % within and between batch coefficients of variation, respectively. There was a good correlation (r = 0.99) between sera TG values by standard method (Enzymic colorimetric) and the present method. The biosensor was unaffected by a number of serum substances at their physiological concentration. Biosensor lost 50 % of its initial activity after its 100 uses over 7 months, when stored at 4 °C.     

K+ Efflux and Retention in Response to NaCl Stress Do Not Predict Salt Tolerance in Contrasting Genotypes of Rice (Oryza sativa L.)

Sudden elevations in external sodium chloride (NaCl) accelerate potassium (K⁺) efflux across the plasma membrane of plant root cells. It has been proposed that the extent of this acceleration can predict salt tolerance among contrasting cultivars. However, this proposal has not been considered in the context of plant nutritional history, nor has it been explored in rice (Oryza sativa L.), which stands among the world’s most important and salt-sensitive crop species. Using efflux analysis with ⁴²K, coupled with growth and tissue K⁺ analyses, we examined the short- and long-term effects of NaCl exposure to plant performance within a nutritional matrix that significantly altered tissue-K⁺ set points in three rice cultivars that differ in salt tolerance: IR29 (sensitive), IR72 (moderate), and Pokkali (tolerant). We show that total short-term K⁺ release from roots in response to NaCl stress is small (no more than 26% over 45 min) in rice. Despite strong varietal differences, the extent of efflux is shown to be a poor predictor of plant performance on long-term NaCl stress. In fact, no measure of K⁺ status was found to correlate with plant performance among cultivars either in the presence or absence of NaCl stress. By contrast, shoot Na⁺ accumulation showed the strongest correlation (a negative one) with biomass, under long-term salinity. Pharmacological evidence suggests that NaCl-induced K⁺ efflux is a result of membrane disintegrity, possibly as result of osmotic shock, and not due to ion-channel mediation. Taken together, we conclude that, in rice, K⁺ status (including efflux) is a poor predictor of salt tolerance and overall plant performance and, instead, shoot Na⁺ accumulation is the key factor in performance decline on NaCl stress.     

In silico Platform for Prediction of N-, O- and C-Glycosites in Eukaryotic Protein Sequences

Glycosylation is one of the most abundant and an important post-translational modification of proteins. Glycosylated proteins (glycoproteins) are involved in various cellular biological functions like protein folding, cell-cell interactions, cell recognition and host-pathogen interactions. A large number of eukaryotic glycoproteins also have therapeutic and potential technology applications. Therefore, characterization and analysis of glycosites (glycosylated residues) in these proteins is of great interest to biologists. In order to cater these needs a number of in silico tools have been developed over the years, however, a need to get even better prediction tools remains. Therefore, in this study we have developed a new webserver GlycoEP for more accurate prediction of N-linked, O-linked and C-linked glycosites in eukaryotic glycoproteins using two larger datasets, namely, standard and advanced datasets. In case of standard datasets no two glycosylated proteins are more similar than 40%; advanced datasets are highly non-redundant where no two glycosites’ patterns (as defined in methods) have more than 60% similarity. Further, based on our results with several algorihtms developed using different machine-learning techniques, we found Support Vector Machine (SVM) as optimum tool to develop glycosite prediction models. Accordingly, using our more stringent and non-redundant advanced datasets, the SVM based models developed in this study achieved a prediction accuracy of 84.26%, 86.87% and 91.43% with corresponding MCC of 0.54, 0.20 and 0.78, for N-, O- and C-linked glycosites, respectively. The best performing models trained on advanced datasets were then implemented as a user-friendly web server GlycoEP (http://www.imtech.res.in/raghava/glycoep/). Additionally, this server provides prediction models developed on standard datasets and allows users to scan sequons in input protein sequences.     

MicroRNA Profiling in Prostate Cancer - The Diagnostic Potential of Urinary miR-205 and miR-214

Prostate cancer (PCa) is the most common type of cancer in men in the United States, which disproportionately affects African American descents. While metastasis is the most common cause of death among PCa patients, no specific markers have been assigned to severity and ethnic biasness of the disease. MicroRNAs represent a promising new class of biomarkers owing to their inherent stability and resilience. In the present study, we investigated potential miRNAs that can be used as biomarkers and/or therapeutic targets and can provide insight into the severity and ethnic biasness of PCa. PCR array was performed in FFPE PCa tissues (5 Caucasian American and 5 African American) and selected differentially expressed miRNAs were validated by qRT-PCR, in 40 (15 CA and 25 AA) paired PCa and adjacent normal tissues. Significantly deregulated miRNAs were also analyzed in urine samples to explore their potential as non-invasive biomarker for PCa. Out of 8 miRNAs selected for validation from PCR array data, miR-205 (p<0.0001), mir-214 (p<0.0001), miR-221(p<0.001) and miR-99b (p<0.0001) were significantly downregulated in PCa tissues. ROC curve shows that all four miRNAs successfully discriminated between PCa and adjacent normal tissues. MiR-99b showed significant down regulation (p<0.01) in AA PCa tissues as compared to CA PCa tissues and might be related to the aggressiveness associated with AA population. In urine, miR-205 (p<0.05) and miR-214 (p<0.05) were significantly downregulated in PCa patients and can discriminate PCa patients from healthy individuals with 89% sensitivity and 80% specificity. In conclusion, present study showed that miR-205 and miR-214 are downregulated in PCa and may serve as potential non-invasive molecular biomarker for PCa.     

Execution of programmed cell death by singlet oxygen generated inside the chloroplasts of Arabidopsis thaliana

Protoplasma - Absorption of excess excitation energy induces overproduction of singlet oxygen (1O2) in plants. The major sources of singlet oxygen production are chlorophyll and its intermediates...