Fine root biomass and tree species effects on potential N mineralization in afforested sodic soils

The study was carried out under three types of plantation forest of 40 years, growing on infertile sodic soils, poor in organic matter and N content, of Indogangetic alluvium at Lucknow (26°45 N; 80°53 E). Fine root biomass estimated under three forests did not differ much with season, or with species (106–113 g m^-2) but varied with soil depth to 0.45 m. The proportion of very fine roots (<0.5 mm) increased with soil depth. Available N in soil was greatest under mixed forest followed by Eucalyptus camaldulensis and Acacia nilotica planted soils. N was maximum in summer season and decreased with soil depth. Nitrogen mineralization during anerobic incubation of 14 days could not be differentiated by tree species, but the monsoon season favoured the process and winter season retarded it. Mineralization decreased with soil depth corresponding to fine roots. There was a reduction in bulk density of soil, pH and EC in forested soil compared to a similar but non forested soil, whereas, organic C and total N increased in forested soils. N mineralization was found to be affected significantly with the fine root biomass and available N content in the soils, whereas negative relations of mineralized N with pH and EC were noticed, though these were not significantly different in this study.     

Duplication of insertion element IS50 associated with Tn5 transposition in Azospirillum brasilense

The characterization of a DNA fragment with a Tn5 insertion in a regulatory nif gene of Azospirillum brasilense is reported. Restriction endonuclease mapping, Southern hybridization with a Tn5 probe, and nucleotide sequencing revealed that IS50 had duplicated in Tn5. The duplication of an IS50 element suggests the occurrence of a replicative mechanism of transposition. A strategy, based on the bacterial ability of homologous recombination that was used to precisely eliminate Tn5 along with the duplicated IS50 element, is presented.     

Studying vertical dependence to improve NFS performance in wireless networks

Wireless networks experience a high level of errors and losses. These physical layer characteristics have an impact on the performance of the higher layers. In addition, the performance of each protocol layer is contingent on the behavior of the other layers. Vertical dependency is a term which describes this inter-dependence between layers. In the wireless and mobile environment, the effects of vertical dependence are particularly pronounced due to the dynamic nature of the environment and due to the fact that traditional assumptions about protocol layer interactions do not always hold. In this paper, we consider the vertical dependencies between various layers in the protocol stack, studying the performance of the Network File System under various error models and improvement techniques. Our experimental results demonstrate the dependency of the application performance on the details of the error characteristics and other protocol layers. After studying the vertical dependencies, we improve NFS performance by implementing changes to the application level reliability mechanisms. Understanding of the vertical dependencies enables development of effective methods for performance enhancement and efficient reaction to errors and changes on the wireless media. This revised version was published online in August 2006 with corrections to the Cover Date.     

Comparative Analysis of Disease-Linked Single Nucleotide Polymorphic Markers from Brassica rapa for Their Applicability to Brassica oleracea

Numerous studies using single nucleotide polymorphisms (SNPs) have been conducted in humans, and other animals, and in major crops, including rice, soybean, and Chinese cabbage. However, the number of SNP studies in cabbage is limited. In this present study, we evaluated whether 7,645 SNPs previously identified as molecular markers linked to disease resistance in the Brassica rapa genome could be applied to B. oleracea. In a BLAST analysis using the SNP sequences of B. rapa and B. oleracea genomic sequence data registered in the NCBI database, 256 genes for which SNPs had been identified in B. rapa were found in B. oleracea. These genes were classified into three functional groups: molecular function (64 genes), biological process (96 genes), and cellular component (96 genes). A total of 693 SNP markers, including 145 SNP markers [BRH—developed from the B. rapa genome for high-resolution melt (HRM) analysis], 425 SNP markers (BRP—based on the B. rapa genome that could be applied to B. oleracea), and 123 new SNP markers (BRS—derived from BRP and designed for HRM analysis), were investigated for their ability to amplify sequences from cabbage genomic DNA. In total, 425 of the SNP markers (BRP-based on B. rapa genome), selected from 7,645 SNPs, were successfully applied to B. oleracea. Using PCR, 108 of 145 BRH (74.5%), 415 of 425 BRP (97.6%), and 118 of 123 BRS (95.9%) showed amplification, suggesting that it is possible to apply SNP markers developed based on the B. rapa genome to B. oleracea. These results provide valuable information that can be utilized in cabbage genetics and breeding programs using molecular markers derived from other Brassica species.     

Antiviral Activity of the Human Cathelicidin,LL-37, and Derived Peptides on Seasonal and Pandemic Influenza A Viruses

Human LL-37, a cationic antimicrobial peptide, was recently shown to have antiviral activity against influenza A virus (IAV) strains in vitro and in vivo. In this study we compared the anti-influenza activity of LL-37 with that of several fragments derived from LL-37. We first tested the peptides against a seasonal H3N2 strain and the mouse adapted H1N1 strain, PR-8. The N-terminal fragment, LL-23, had slight neutralizing activity against these strains. In LL-23V9 serine 9 is substituted by valine creating a continuous hydrophobic surface. LL-23V9 has been shown to have increased anti-bacterial activity compared to LL-23 and we now show slightly increased antiviral activity compared to LL-23 as well. The short central fragments, FK-13 and KR-12, which have anti-bacterial activity did not inhibit IAV. In contrast, a longer 20 amino acid central fragment of LL-37 (GI-20) had neutralizing activity similar to LL-37. None of the peptides inhibited viral hemagglutination or neuraminidase activity. We next tested activity of the peptides against a strain of pandemic H1N1 of 2009 (A/California/04/09/H1N1 or “Cal09”). Unexpectedly, LL-37 had markedly reduced activity against Cal09 using several cell types and assays of antiviral activity. A mutant viral strain containing just the hemagglutinin (HA) of 2009 pandemic H1N1 was inhibited by LL-37, suggested that genes other than the HA are involved in the resistance of pH1N1. In contrast, GI-20 did inhibit Cal09. In conclusion, the central helix of LL-37 incorporated in GI-20 appears to be required for optimal antiviral activity. The finding that GI-20 inhibits Cal09 suggests that it may be possible to engineer derivatives of LL-37 with improved antiviral properties.     

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO₄, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.     

Proteomic Profiling of SupT1 Cells Reveal Modulation of Host Proteins by HIV-1 Nef Variants

Nef is an accessory viral protein that promotes HIV-1 replication, facilitating alterations in cellular pathways via multiple protein-protein interactions. The advent of proteomics has expanded the focus on better identification of novel molecular pathways regulating disease progression. In this study, nef was sequenced from randomly selected patients, however, sequence variability identified did not elicited any specific mutation that could have segregated HIV-1 patients in different stages of disease progression. To explore the difference in Nef functionality based on sequence variability we used proteomics approach. Proteomic profiling was done to compare the effect of Nef variants in host cell protein expression. 2DGE in control and Nef transfected SupT1 cells demonstrated several differentially expressed proteins. Fourteen protein spots were detected with more than 1.5 fold difference. Significant down regulation was seen in six unique protein spots in the Nef treated cells. Proteins were identified as Cyclophilin A, EIF5A-1 isoform B, Rho GDI 1 isoform a, VDAC1, OTUB1 and α-enolase isoform 1 (ENO1) through LC-MS/MS. The differential expression of the 6 proteins was analyzed by Real time PCR, Western blotting and Immunofluorescence studies with two Nef variants (RP14 and RP01) in SupT1 cells. There was contrasting difference between the effect of these Nef variants upon the expression of these six proteins. Downregulation of α-enolase (ENO1), VDAC1 and OTUB1 was more significant by Nef RP01 whereas Cyclophilin A and RhoGDI were found to be more downregulated by Nef RP14. This difference in Nef variants upon host protein expression was also studied through a site directed mutant of Nef RP01 _{(55AAAAAAA61)} and the effect was found to be reversed. Deciphering the role of these proteins mediated by Nef variants will open a new avenue of research in understanding Nef mediated pathogenesis. Overall study determines modulation of cellular protein expression in T cells by HIV-1 Nef variants.