Transcriptome based Identification of silver stress responsive sRNAs from Bacillus cereus ATCC14579.

Microbes modulate their metabolic and physiological mechanisms in response to changing environmental conditions. It is our interest to identify small regulatory RNAs using microarray expression data (GSE26043) obtained from B. cereus ATCC 14579 in AgNO3 stress. By definition, expression of transcripts from the Intergenic Regions (IGR) with >=2 fold under silver stress is predicted as novel small RNAs. Computational analysis of the IGR expression levels extracted from the available microarray data help in the identification of stress responsive sRNAs with rare promoters (Sigma 24, 28, 32, 54 and 70) followed by terminator signals predicted using the sRNAscanner tool. We predicted 1512 sRNA specific regions on both positive and negative strands collectively. Thus, a non-redundant high scoring unique 860 sRNAs with distinct promoter (S24: 83, S28: 86, S32: 31, S54: 57, S70: 223, sRNA_specific_S70: 380) and terminator signals are reported. These unique computationally predicted sRNA regions were verified with the highly expressing IGRs from the microarray data. It should be noted that 14 sRNAs reported in earlier studies were also found in this dataset. This study has reported 71 additional sRNAs from the transcriptome under metal stress response. Hence, we use global transcriptomics data for the identification of novel sRNAs in B. cereus. We described a general model using a procedure for the identification of small regulatory RNAs using microarray expression data with appropriate cross validation modules. It is found that some sRNAs reported in this study were found to have multiple rare promoters. This opens the possibility of sRNA activation under multiple stress condition. These sRNA data reported in this study should be characterized for their mRNA targets and molecular functional networks in future investigations.

Qualitative and Quantitative Estimation of Bacterial Lipid Production.

An ever increasing energy demand and fast depletion of fossil fuels have led to increased consideration of bacterial lipids as a renewable biofuel source. Many methods are available for both physical and chemical extraction of bacterial lipids. The method of choice will depend on the nature of sample to be analyzed, combinations of solvent systems preferred, content and quality of the lipid to be analyzed, types of equipment available, and time of the extraction procedures employed. Here we describe the most reliable, routine method of extracting bacterial lipids and evaluating the growth kinetic parameters like biomass and lipid productivity and lipid content. We also describe the method of comparing bacterial fatty acid methyl ester peaks with standard peaks for analysis.

Assessment of Fuel Quality Parameters and Selection of Bacteria Using PROMETHEE-GAIA Algorithm.

Recently, biodiesel is gaining significant importance due to eco-friendly nature and development of large-scale production methodologies. Biodiesel is a mixture of mono-alkyl esters of fatty acids (FA). During transesterification, the long-chain FAs are combined with methanol to produce fatty acid methyl ester (FAME), the principle component of biodiesel. The biodiesel fuel properties are determined by structural components of FAs such as chain length, degree of unsaturation, and branching of the carbon chain. The fuel quality of biodiesel are evaluated by assessing the properties such as cetane number (CN), iodine value (IV), cold filter plugging point (CFPP), higher heating value (HHV), cloud point (CP), pour point (PP) etc., of FAME. The amount of lipid or fat produced may vary from organism to organism. A particular species may have high biomass with low lipid content and vice versa. So the selection of suitable species/genus by decision analysis software is much needed. Besides various multi-criteria decision analyses, Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) and Graphical Analysis for Interactive Aid (GAIA) analysis is considered as the most promising tool in selecting the prominent biodiesel producing strain. Here we describe the method of evaluating the fuel quality parameters for the produced FAME and selecting the prominent strain through PROMETHEE-GAIA algorithm.

Growth kinetic and fuel quality parameters as selective criterion for screening biodiesel producing cyanobacterial strains.

The efficiency of cyanobacterial strains as biodiesel feedstock varies with the dwelling habitat. Fourteen indigenous heterocystous cyanobacterial strains from rice field ecosystem were screened based on growth kinetic and fuel parameters. The highest biomass productivity was obtained in Nostoc punctiforme MBDU 621 (19.22mg/L/day) followed by Calothrix sp. MBDU 701 (13.43mg/L/day). While lipid productivity and lipid content was highest in Nostoc spongiaeforme MBDU 704 (4.45mg/L/day and 22.5%dwt) followed by Calothrix sp. MBDU 701 (1.54mg/L/day and 10.75%dwt). Among the tested strains, Nostoc spongiaeforme MBDU 704 and Nostoc punctiforme MBDU 621 were selected as promising strains for good quality biodiesel production by Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis.

Unraveling the presence of multi-class toxins from Trichodesmium bloom in the Gulf of Mannar region of the Bay of Bengal.

Trichodesmium is an enigmatic bloom forming, non-heterocystous cyanobacterium reported most frequently in the coastal waters of India. However, the toxigenic potential of this globally significant N2 fixing cyanobacterium has not been characterized. In this study, we report for the first time the presence of potent multi-class neurotoxins such as Anatoxin-a, Saxitoxins, Gonyautoxin and hepatotoxins like MC-LR, MC-YA from a bloom material of Trichodesmium sp. MBDU 524 collected at the Gulf of Mannar region. Toxins were determined using liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) analysis of HPLC purified aqueous and solvent fractions. Molecular phylogenetic analysis through 16S rRNA gene sequencing showed the close relationship with Trichodesmium erythraeum clade. The toxigenic potential was validated through brine shrimp toxicity assay and showed 100% mortality after 48 h of incubation. The results suggest the potential toxigenic and environmental impacts of Trichodesmium bloom sample from the Gulf of Mannar region.