PANDYA, P. R.THUBE, HARSHALA A.2018-05-252018-05-252008http://krishikosh.egranth.ac.in/handle/1/5810047525Methane (CH4) eructated from ruminants represents a loss of 8 to 13% of the digestible energy ingested by the animal and contributes to global warming. Decreasing methane emissions from ruminant livestock is desirable in order to both, reduce greenhouse gases in the atmosphere and improve energy capture during digestion. Nutritionists have been trying for a long time to mitigate rumen methane emissions in order to enhance animal performance. The methods most commonly attempted involve elimination of ciliate protozoans which support methanogen populations, and addition of acetogenic bacteria to rumen fluid. The key steps for developing successful methane abatement strategies are likely to be steps which exploit natural processes in the rumen. Therefore, the specific role of an individual rumen methanogens is important as it has to compete with the other microbes of the eco-system for its survival. The enumeration of a specific species of methanogenic bacteria in the ecosystem (to quantify its role in rumen fermentation) is difficult with the conventional techniques due to large number of biochemical tests to be performed and imprecision of the technique even for the most predominant microbe present in the ecosystem. The application of molecular techniques has already revealed the enormous wealth of microbial diversity and putative novel species in the rumen. Present study aimed at exploring diversity of rumen methanogens in buffalo by molecular approach. Three adult buffalo were maintained on maintenance ration as per ICAR, 1998) feeding standards, continuously for three weeks. Samples of Rumen liquor (about 500 ml) were collected from three buffaloes at 0, 2 and 4 h after feeding by a suction pump using a flexible stomach tube. Samples were filtered through four layers of cheesecloth. The strained rumen liquor was used for the microbial study. The bacterial DNA was isolated following enzyme-chemical lysis method. The DNA stock samples were quantified using Nano-drop spectrophotometer at 260 and 280 nm using the convention that one absorbance imit at 260 nm wavelength equals 50 µg DNA per ml. The Ultra violet absorbance was checked at 260 and 280 nm for determination of DNA concentration and purity. Purity of DNA was judged on the basis of optical density ratio at 260:280 nm which was between 1.8 to 2.0 for all the samples indicating desirable purity. Concentration of DNA was estimated using the formula : Concentration of DNA (mg/ml) = OD 260 x 50 x Dilution factor. Quality and purity of DNA were also checked by agarose gel electrophoresis. Universal primer pair (Met 86F 5'ACA GGC CTA ACA CAT GCA AGT C-3'and Met 1340R 5'AGG GCG G (AT) GTG TAC AAG GC-3') for methanogens targeting 16S rRNA gene were used for amplification of DNA. The amplified product was visualized as a single compact band of expected size under UV light and revealed amplicons of 1200 bp size when documented by gel documentation system. The PCR products after purification were ligated in pDrive vector followed by transformation into competent cells (DH5-α strain) of E.coli. One hundred fifty white recombinant colonies were obtained out of which 133 were randomly selected, revived on another plates and screened for expected insert by colony PCR. Recombinant colonies were inoculated in Luria Broth for 16-18 hrs. Plasmid extraction from overnight culture was carried out by alkaline lysis method. The concentration of the plasmid was determined and was subjected to automated DNA sequencing on ABI PRISM® 310 Genetic Analyzer (Applied Biosystems, USA). Sequencing was carried out using BigDye Terminator v3.1 Cycle sequencing kit. Sequences obtained were in the range of 400 to 800 base pairs. Sequences after cleaning (removal of primer and vector sequence) were searched against BLASTn database to find similarity matches. Phylogenetic analysis was carried out by DNADIST with neighbor joining method and DNA Parsimony available at PHYLIP 3.5c package. The tree was mainly divided in to 4 major clusters viz. Methanomicrobia group, Thermoplasmata group, Methanobacteriales group, and Unidentified group. Out of 132 clones, 41.22% showed similarity with Methanomicrobia, with two sub groups Methanoculleus (51.85%) and Methanosarcina (48.15%) in DNA DIST. How ever, in DNA Parsimony analysis, over and above these two subgroups, a group of clones (38.89% clones) was observed which did not share high similarity with any known genus and grouped as unidentified Methanomicrobia. Eighteen (13.6%) clones grouped with Thermoplasmata group in both the trees. The smallest group was of Methanobacteriales with 12.12% and 3.8% clones in DNA DIST and DNA Parsominy analysis, respectively. Our library also uncovered a novel group of rumen archaeal sequences which includes 44 (33.33%) clones in DNA DIST and 57 (43.18%) clones in DNA Parsimony and did not form close cluster with any of cultured and uncultured sequences in both the trees and remained as unidentified methanogens which are supposed to be new. All sequences were submitted to Genbank and are available with the accession numbers EU794740-EU794854, EU814699-EU814714 in EMBL, GenBank and DDBJ Nucleotide Sequence Databases.enANIMAL NUTRITION, AGRICULTURECHARACTERIZATIONThesis