Informatics Publishing Limited

K. G. Purushotham ¹, P. Arun ², J. Johnsy Jayarani ², R. Vasanthakumari ², D. Chamundeeswari ³

Affiliations
1 Department of Industrial Biotechnology, Dr. M. G. R. Educational and Research Institute, Dr. M. G. R .University, Maduravoyal, Chennai-600 095, Tamil Nadu, IN
2 Dr. M.G.R. Educational and Research Institute, Dr. M. G. R University, Maduravoyal, Chennai-600 095, Tamil Nadu, IN
3 Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, IN

Abstract

Medicinal plants are potential of antimicrobial compounds. The present study deals with the antibacterial and antifungal activity of methanolic extracts of Tectona grandis (Verabinaceae) leaves were collected from the garden of Dr. M.G.R. University during May- June 2009, Chennai, India. Air- dried and extracted by methanol. The methanolic extract of Tectona grandis leaves were examined for antibacterial and antifungal activity by in vitro using the disc diffusion method, Minimum Inhibitory Concentration (MIC), Minimum Bactericidal Concentration (MBC) and Minimum fungicidal Concentration (MFC). Activity against Gram-positive (Streptococcus species (MTCC 389)), Gram-negative bacteria (Klebsiella pneumonia (MTCC 432), Psedomonas aeruginosa (MTCC 1688), Proteus mirabilis (MTCC 425), Escherichia coli, (MTCC 729), Salmonella typhimurium(MTCC 98))and fungal strains (Candida albicans, Cryptococcus neoformans, Aspergillus flavus, Aspergillus niger Aspergillus fumigatus Rhizopus sp. Trichophyton rubrum,Trichophyton gypseum and Trichophyton mentagrophytes) is discussed.

Keywords

Antibacterial Activity, Antifungal Activity, Disc Diffusion Method, MIC, MBC, MFC, Tectona grandis.

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P. Arun ¹, K. G. Purushotham ², Johnsy Jayarani ², Vasantha Kumari ², D. Chamundeeswari ³

Affiliations
1 Department of Industrial Biotechnology, Dr. M.G.R. Educational and Research Institute, Dr. M.G.R. University, Maduravoyal, Chennai-600 095 Tamil Nadu, IN
2 Dr.M.G.R.Educational and Research Institute, Dr. M. G. R University, Maduravoyal, Chennai-600 095, Tamil Nadu, IN
3 Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, IN

Abstract

Lawsonia inermis known as Henna is a woody and flowering plant found in North Africa and South west Asia. Its leaves extensively in the treatmernt of urinary tract infection in Siddha system of medicine. Lawsonia inermis was subjected to antibacterial analysis. A battery of assays were performed on different extracts of Lawsonia inermis (Henna) for antibacterial activities. Antibacterial effects of n-hexane, choloroform and methanol extracts of the leaves extract of Lawsonia inermis exhibited various degree of inhibition activity. It was observed that leaves extract were promising against gram positive and gram negative bacteria viz. Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli and Proteus mirablis. This study showed that Lawsonia inermis could inhibit certain bacteria.

Keywords

Anti-Bacterial Activity, Lawsonia inermis, Henna and Medicinal Plants.

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Puniethaa Prabhu ¹, P. Arun ¹, Ashaq Hussain Bhat ¹, B. Kalpana ²

Affiliations
1 Department of Biotechnology, K.S.Rangasamy College of Technology, Tiruchengode – 637 215, IN
2 Department of Biotechnology, K.S.Rangasamy College of Technology, Tiruchengode – 637 215, IN

Abstract

The study of 16s rRNA sequences through Next Generation Sequencing (NGS) have revolutionized the understanding of the microbial community composition and its structure. The massive data production and substantial cost reduction in NGS technologies have led to rapid growth of metagenomic research both quantitatively and qualitatively. Soil Metagenomics is a discipline that enables the genomic study of uncultured organisms in the soil samples. Quantitative Insights Into Microbial Ecology (QIIME) and Cloud Virtual Resource (CloVR) processes metagenomic data from a high-throughput 16S rRNA sequencing platform, beginning with multiplexed sequence reads, then Operational taxonomic units picking, Summarizing taxonomies, phylogenetic relationships and analyzing the alpha and finally beta diversities through plots. The proposed study demonstrates the analysis of microbial composition present in the study sample using QIIME and CloVR metagenomic pipelines. The soil metagenomic Datasets applied for the present study are retrived from European Nucleotide Archive (ENA) under the sample ID ERP001958.The interrealtionships among the OTUs is studied through the network analysis. A comparative analysis of the metagenomic pipelines is also performed with the gene clustering algorithms for understanding the concept of OUT clustering in metagenomic analysis. This research underscores the usefulness of next-generation sequencing techniques both to understand the ecological impact of contamination and to identify potential molecular proxies for detection of natural attenuation.

Keywords

NGS Data Analysis, Soil Microbiome, OTU Clustering, Diversity and Taxonomy Relationships.

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P. Arun ¹, K. Iyakutti ²

Affiliations
1 Madurai Kamaraj University, Madurai-625021, Tamil Nadu, IN
2 School of Physics, Madurai Kamaraj University, Madurai-625021, Tamil Nadu, IN

Abstract

With an increasing continuous growth of information in WWW it is very difficult for the users to access the interested web pages from the website. Because day by day the information in the web is growing in an increasing manner so without any help system the user may spend more time to get the interested information from the website. To overcome the above problem, in this paper we propose a Model which create a User Interested Page Ontology (UIPO), it will be created by assigning weights and ranking the user interest by count the number of occurrence of each item which was collected from the web logs within a session for all users. The main feature of this model is, it generates UIPO dynamically from that it personalize the interested pages to the web users in their next access The proposed model is very useful for understanding the behavior of the users and also improving the web site design too. The performance of the new model in a session is also discussed in this paper.

Keywords

Web Usage Mining, Web Logs, Ontology, Session, Web Personalization.

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