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.     

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.     

The Embedding Problem for Markov Models of Nucleotide Substitution

Continuous-time Markov processes are often used to model the complex natural phenomenon of sequence evolution. To make the process of sequence evolution tractable, simplifying assumptions are often made about the sequence properties and the underlying process. The validity of one such assumption, time-homogeneity, has never been explored. Violations of this assumption can be found by identifying non-embeddability. A process is non-embeddable if it can not be embedded in a continuous time-homogeneous Markov process. In this study, non-embeddability was demonstrated to exist when modelling sequence evolution with Markov models. Evidence of non-embeddability was found primarily at the third codon position, possibly resulting from changes in mutation rate over time. Outgroup edges and those with a deeper time depth were found to have an increased probability of the underlying process being non-embeddable. Overall, low levels of non-embeddability were detected when examining individual edges of triads across a diverse set of alignments. Subsequent phylogenetic reconstruction analyses demonstrated that non-embeddability could impact on the correct prediction of phylogenies, but at extremely low levels. Despite the existence of non-embeddability, there is minimal evidence of violations of the local time homogeneity assumption and consequently the impact is likely to be minor.     

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...     

Screening of antifungal activity of various plant leaves extracts from Indian plants

The present study was designated to evaluate the antifungal activity and to root out the antifungal plant leaf extracts from this Indian folk-flore. The in vitro antifungal assay was performed by agar diffusion test and minimum inhibitory concentration (MIC) for hexane, ethyl acetate, methanol and distilled water plant leaf extracts. Extraction of 17 different plant leaves was carried out in different solvents such as hexane, ethyl acetate, methanol and distilled water. Among them extractive yield of methanol was maximum than the rest of the three solvents. These extracts were screened for their antifungal activity against nine different fungi. Among these ethyl acetate extracts of Adhatoda vasica, Ocimum sanctum and Holoptelea integrifolia exhibited maximum antifungal activity against Alternaria sp., Aspergillus parasi, Aspergillus nidulans, Trichoderma harzianum and Aspergillus flavus with MIC of 80, 40 and 20 ppm against Aspergillus nidulans and Alternaria sp. Ethyl acetate extracts showed promising antifungal activity against Adhatoda vasica, Ocimum sanctum and Holoptelea integrifolia against Aspergillus nidulans, and Alternaria sp. might be applicable as fungicide against fungal plants disease.     

Combination of sulfamethoxazole and selenium in anticancer therapy: a novel approach

Sulfonamides have been reported to possess substantial antitumor activity as they act as carbonic anhydrase inhibitors. In addition, selenium appears to have a protective effect at various stages of cancer due to its antioxidant property, enhanced carcinogen detoxification, inhibition of cell invasion, and by inhibiting angiogenesis. Here, in the present study we aimed to evaluate and synergize the cytotoxic activity of sulfonamide and selenium (SM+SE) as effective therapy in the treatment of DENA-induced HCC. Hepatocarcinogeneis was induced by a single intraperitoneal injection of diethylnitrosamine (DENA) (200 mg/kg) in phosphate buffer. 30 Male Wistar rats used in this study were divided randomly into five equal groups (n = 6). DENA-administered animals showed significant alteration (p < 0.001) in liver-specific enzymes—glutamate oxaloacetate transaminase (SGOT), serum glutamate pyruvate transaminase (SGPT), alkaline phosphatase (ALP), and Alpha fetoproteins (AFP), and also induced severe histopathological changes in the hepatic tissues. Interestingly, treatment with (SE+SE) (SM 30 mg/kg + SE 3 mg/kg) significantly reduced (P < 0.001, P < 0.001, P < 0.001, P < 0.001) the elevated AFP, SGOT, SGPT, and ALP levels, respectively, suggesting that combination therapy of SM+SE has a potential to treat DENA-induced liver damage.