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Metagenomics is the study of uncultivable microorganisms to find the diversity and exploitation of microbial communities present in complex ecosystem. Only less than 1% of the microorganisms present in the world can be cultured. Rest of the microorganisms cannot be cultured due to unavailability of culture conditions or incomplete knowledge of their nutrient requirement and also due to incomplete knowledge of their symbiosis with other organisms. Symbiosis is the process by which these microorganisms utilize the metabolites produced by each other. The inability to culture due to incorrect combination of temperature, pressure or atmospheric gas composition, lack of necessary symbionts, lack of nutrients or surface, accumulation of toxic waste products from their own metabolism and intrinsically slow growth rate or rapid dispersion from colonies.
In most countries the municipal solid waste (MSW) disposed at landfill sites. MSW leachate receives a mixture of municipal, commercial and mixed industrial waste. It contained four types of pollutants which are dissolved organic matter, inorganic macrocomponents, heavy metals and xenobiotic organic compounds. In these sites all the waste of the city is collected which include organic compounds, paper and card, plastic, leather, metal, glass, textiles, ash and unclassified wastes and it is then processed. MSW leachate is the liquid that percolates through the municipal solid waste. Excess of rainwater percolates through waste layers in a landfill generates MSW leachate. Many processes such as microbial, chemical and physical in combination transfers pollutants from the waste to the leachate. It is composed of many hazardous as wells as non-hazardous substances. Because leachate has many chemical substances present in it and also present are many types of nutrients in it. So it provides an extreme environments for growth of many microorganisms and also it is known that toxic substances like benzene, toluene, phenol, ethylebenzene, phthalate, dichloroethane and trichloroethane are present in municipal solid waste leachate. So it is hypothesized that the microorganisms found in leachate may have some novel genes which can degrade toxic substances like phthalate, dichloroethane or trichloroethane. This happens because the microorganisms have the ability to adapt in the environment in which they live.
Ground water contamination is one of the major problems nowadays. The compounds which affect water quality adversely are mainly volatile organic chemicals. The most common of these compounds are halogenated solvents. These halogenated compounds are persistent for long time. Many of these halogenated compounds are toxic and carcinogenic for animals. It has been reported that the half life of trichloroethylene is 300 days and it is suspected carcinogen in rats. 1,2 Dichloroethane (DCE), commonly known as ethylene dichloride, is a chlorinated hydrocarbon. It is mainly used for the production of vinyl chloride monomer and also major precursor for polyvinyl chloride production. It is also used as an intermediate for other organic chemical compounds. EDC is toxic due to its high vapour pressure. EDC is highly unstable in the presence of alluminium metal and when moist with zinc and iron. It is highly soluble in and it has a half-life of 50 years. Due to its very long half-life. It is not easily degradable. Trichlorethylene is a major industrial solvent used for degreasing and cleaning metal parts and electronic components. The waste generated from all these processes entered into the environment. It is the most common contaminant found at the hazardous waste site.
This study is conducted to find novel genes through metagenomics approach which can degrade toxic substances such as, dichloroethane, tricholoroethane etc., present in the municipal solid waste leachate.
Isolation and characterization of novel toxicant degrading genes from Municipal Solid Waste leachate using metagenomics approach.
Microcosm experiment set up and analysis of degradation products using HPLC / GC analysis
Metagenomic DNA isolation, construction and screening of metagenomic library for positive clones
Sequencing of positive clones and analysis of sequencing data using bioinformatics tools
REVIEW OF LITERATURE
Metagenomics has been defined as function-based or sequence-based cultivation-independent analysis of the collective microbial genomes present in a given habitat (Riesenfeld et al. 2004). This rapidly growing research area provided new insights into microbial life and access to novel biomolecules (Banik and Brady 2008; Edwards et al. 2006; Frias-Lopez et al. 2008; Venter et al. 2004). Recently, advances in throughput and cost-reduction of sequencing technologies have increased the number and size of metagenomic sequencing projects, such as the Sorcerer II Global Ocean Sampling (GOS) (Biers et al. 2009; Rusch et al. 2007), or the metagenomic comparison of 45 distinct microbiomes and 42 viromes (Dinsdale et al. 2008). So far, the main application area of metagenomics is mining of metagenomes for genes encoding novel biocatalysts and drugs (Lorenz and Eck 2005).To explore the microbial diversity of environmental samples, also termed "taxonomical binning," different approaches can be applied (Richter et al. 2008). Usually, phylogenetic relationships are determined by analysis of conserved ribosomal RNA (rRNA) gene sequences (Woese 1987). Extensive sequencing of ribosomal RNA genes resulted in generation of several large reference databases, such as the ribosomal database project (RDP) II (Cole et al. 2003), Greengenes (DeSantis et al. 2006), or SILVA (Ludwig et al. 2004). Direct sequencing of metagenomic DNA has been proposed to be the most accurate approach for assessment of the taxonomic composition (von Mering et al. 2007). In addition, Manichanh et al. (2008) showed that evaluation of a shotgun sequencing-derived dataset provides a reliable estimate of the microbial diversity stored in metagenomics libraries. Venter et al. (2004) were the first to apply whole genome shotgun sequencing to samples of the Sargasso Sea in order to characterize the microbial community and identify new genes and species. The dataset included 1.66 million sequences comprising 1.045 billion base pairs. The taxonomic composition was evaluated by 16S rRNA gene analysis and employment of alternative Phylogenetic markers such as RecA/RadA, heat shock protein Hsp70, elongation factor Tu, and elongation factor G. The assignment to phylogenetic groups was consistent among the different markers but the abundance of the encountered phylogenetic groups varied (Venter et al. 2004). Determination of the taxonomic diversity by analysis of pyrosequencing- or shotgun-derived datasets has been applied to various environments, including an acid mine biofilm (Tyson et al. 2004), seawater samples (Angly et al. 2006; DeLong et al. 2006), the Soudan mine (Edwards et al. 2006), the Peru Margin subsea floor (Biddle et al. 2008), honey bee colonies (Cox-Foster et al. 2007) The above-mentioned tools have been successfully employed for characterization of several habitats such as the Sargasso Sea and sludge used in industrial wastewater processing (Abe et al. 2005; McHardy et al. 2007). According to Huson et al. (2009), up to 90% of the sequences of a metagenomics dataset may remain unidentified due to the lack of a reference sequence. Large-scale sequencing of metagenomic DNA permits the identification of the most frequently represented functional genes and metabolic pathways that are relevant in a given ecosystem. In this way, the dominant biosynthetic pathways and primary energy sources can be assessed. Edwards et al. (2006) conducted the first study in which metabolic profiles of whole microbial communities based on a pyrosequencing derived dataset were analyzed. Other examples for identification of the functional diversity and profiles by analysis of pyrosequencing-derived datasets include an obesity-associated gut microbiome (Turnbaugh et al. 2006), a coral-associated microbial community (Wegley et al. 2007), a comparison of nine biomes (Dinsdale et al. 2008), ocean surface waters (Frias-Lopez et al. 2008), the Peru Margin subseafloor (Biddle et al. 2008), coral atolls (Dinsdale et al. 2008), and stressed coral holobionts (Thurber et al. 2009).Most biocatalysts employed for biotechnological or industrial purposes are of microbial origin. This reflects the fact that the broadest genetic variety in the biosphere can be found in the different microbial communities present in the various ecosystems on earth (Ferrer et al. 2009). The application of culture-independent metagenomic approaches allows exploiting this almost unlimited resource of novel biomolecules (Sjöling and Cowan 2008). To identify enzymatic functions of individual clones, chemical dyes and insoluble or chromophore-containing derivatives of enzyme substrates can be incorporated into the growth medium (Daniel 2005; Ferrer et al. 2009; Handelsman 2004). Examples for this simple activity-based approach are the detection of recombinant E. coli clones exhibiting protease activity on indicator agar containing skimmed milk as protease substrate (Lee et al. 2007; Waschkowitz et al. 2009) or the detection of lipolytic activity by employing indicator agar containing tributyrin or tricaprylin as enzyme substrates (Hårdeman and Sjöling 2007; Heath et al. 2009; Lee et al. 2006). Clones with proteolytic or lipolytic activity are identified by halo formation on solidified indicator medium.
Recently many biocatalysts have been discovered through metagenomics approach, these include lipases (Hardeman and Sjoling 2007, Meilleur et al 2009, Wei et al 2009, Voget et al 2003, Lee et al 2006), Esterase (Rhee et al 2005, Rees et.al 2003,Heath et al. 2009, Li et al. 2008, Wu and Sun 2009), cellulose (Rees et al. 2003, Voget et al. 2006, Pottkamper et al. 2009, Duan et al . 2009, Feng et al. 2007), protease (Waschkowitz et al.2009, Lee et al. 2007), antibiotics (Brady and Clardy 2004).
MATERIALS AND METHODS :
Samples used: The environmental sample used for this study is municipal solid waste leachate collected from various landfill sites.
Microcosms preparation : Microcosms will be prepared using 100ml serum bottles with 10 - 50 ppm of 1,2 Dichloroethane amended with sodium lactate as electron donor and also with cysteine, vitamin B12, hepes and yeast extract. Autoclaved control microcosms will also be prepared and supplemented with benzalconium chloride. All the microcosms will be immediately sealed with rubber stoppers and aluminum crimp seals. All the microcosms will be incubated in the dark at 23 Â°C (Marzorati et al 2010 ).
Measurement of dichloroethane degradation: The possible degradation products of dichloroethane like ethane and vinyl chloride will be analyzed using headspace gas chromatography. The headspace chromatography will be done using gas chromatograph flame ionization detector (GC - FID ) and capillary column. The temperature of the injector will be 200 Â°C with split ratio of 5 and the temperature of the detector will be 250 Â°C. Helium will be used as the carrier gas at a flow rate of 3 mL/min. The limit of detection will be about 1-2 Âµg/L (Marzorati et al 2010 ).
In silico PCR detection of the Reductive Dehalogenase ( RDs ) : The amino acid sequence of the Reductive Dehalogenase enzyme of the sixty microorganisms were downloaded from the NCBI. Using the above organism's amino acid sequences multiple sequence alignment using the program ClustalW via Jalview was done. In the multiple sequence alignment result we got a conserved region ranging from 517 to 641. We divided the conserved region in the seven regions designated as : Conserved region 1 - 6 and region for the sake of simplicity. We found that the amino acids in the region 1 ( 592 - 625 ) were more conserved than in the other regions. We designed six sets of degenerate primers from this region. For designing the primer from alignment result, we selected the most conserved amino acid from each of the species in the region 1. Then we converted the amino acid sequence to nucleotide sequence using the degeneracy codes. Followed by combining these codons to form primers. In this process we were able to make three forward primers and two reverse primers. The program Gene Runner was used to calculate Tm, GC % and for analysis of different characteristics of primers like hairpin loop formation, dimer formation, bulk loop formation and internal loop formation. After applying all the above procedures we found six set of primers appropriate for the amplification of the reductive dehalogenase gene from our sample, municipal solid waste leachate. In silico PCR was done to check the efficiency of the primers designed.
Metagenomic DNA extraction : For the extraction of metagenomic DNA following protocol is used. Extraction of metagenomic DNA from municipal solid waste leachate is done by using fast DNA spin kit for soil supplied by MP Biomedicals as follow. 978Î¼l sodium phosphate buffer and 122 Î¼l MT buffer is added to 500mg of soil sample in a lysing matrix E tube. After homogenization centrifuged at 14,000 x g for 5-10 minutes to pellet debris. After transferring the supernatant to a clean centrifuge tube, 250 Î¼l PPS is added followed by shaking to precipitate the proteins. Then centrifugation is done at 14,000 x g for 5 minutes to pellet the precipitate and supernatant is transferred to a 15ml tube. To the supernatant 1ml of binding matrix is added and placed on rotator, then 600Î¼l of the resuspended supernatant is transferred to the SPINâ„¢ Filter and centrifuged at 14,000 x g for 1 minute. The same procedure is repeated to filter whole solution. The SPINâ„¢ Filteris air dried at room temperature for 5 minutes. Then 50-100 Î¼l of DES (DNase/Pyrogen-Free Water) is added and centrifuged.
Construction of a metagenomic library : The metagenomic DNA will be partially digested with Sau3AI and will be ligated to BamHI digested and dephosphorylated p18GFP. Then the recombinant p18GFP will be transformed in the competent E. coli cells. After the transformation, the cells will be incubated in SOC medium at 37Â°C for 1 hour with gentle rotation followed by addition of ampicillin and incubation at 37Â°C at 200 rpm in incubator shaker. Then this culture will be plated on ampicillin plate containing 0.5mM of IPTG and will be placed in incubator overnight at 37Â°C. Next day grow the colonies from the plate in a LB medium containing ampicillin. The plasmid will be extracted from the culture and the size of the inserted DNA fragment will be analyzed by restriction enzyme digestion (Uchiyama T. et al 2010).
(a) Screening of positive clones by flow sorting : An aliquot from the metagenomic libraray will be grown in LB medium containing ampicillin at 30 Â°C and 200 cycles min-1 . GFP expression will be induced by adding ( 0.5mM ) IPTG. The cells from the metagenomic library will be applied to the flow cytometer. The efficiency of the sorting will be analyzed by flow cytometry. In the sorted fraction a ratio of non-fluorescent cells to total cells should be increase significantly. The cells will be grown in LB medium containing ampicillin at 37 Â°C and 200 cycles min-1. This culture will again be checked using flow cytometry, if the cells with high fluorescence signal (a fluorescence value > 80) will abundantly present then above steps will be repeated. Aliquot from the above culture will be grown in LB medium containing ampicillin at 30 Â°C and 200 cycles min-1 untill the OD600 reaches 0.6-0.8. The GFP expression will be induced by adding induction substrate (Dichloroethane ) at a final concentration of 2mM and growing culture at 30 Â°C and 200 cycles min-1 overnight . The overnight culture will be applied to the flow cytometer and a sorting region will be set to collect the GFP expressing cells. Sorting region will also be set for the cells without GFP fluorescence. The cells in the without GFP fluorescence region will be used for the induction assay with another substrate. The sorted cells will be grown at 30 Â°C and 200 cycles min-1 untill the OD600 reaches 0.6-0.8. The culture will be divided into two fractions, one which will be supplemented with the induction substrate and both the fraction will be incubated at 30 Â°C and 200 cycles min-1. On the next day the fluorescence intensities of both the fractions will be compared using flow cytometry. Induction efficiency will be calculated using the following formula : Efficiency = (mean fluorescence intensity of the induced culture)/(mean fluorescence intensity of the noninduced culture). The plasmid DNA will be extracted from positive clone using standard plasmid extraction procedure. The positive clones will be sent for sequencing (Uchiyama T et al 2010).
(b) Screening of positive clones by microarray :
Constrution of fosmid library : For the screening of positive clones, fosmid library will be constructed first.The fosmid library will be constructed using the CopyControl TM Fosmid Library Production Kit according to manufacturer protocol. Purified DNA will be treated with end repair enzyme mix to generate blunt ends and then will be ligated into the fosmid vector pCC1FOS. After in vitro packaging into lambda phages and then transfection into Escherichia coli, the bacterial cells will be plated on Luria-Bertanin containing 12.5Âµg/ml chloramphenicol. The plates will be incubated at 37Â Â°Â C for 24 hr prior to the selection of colonies. The transfected cells will be transferred to 96 well plates containing 12.5 5Âµg/mL chloramphenicol containing LB liquid medium with induction solution and will be incubated at 37Â Â°Â C for 24 hr. The plates will be replicated into deep 96-wll plates with 1.5 mL of LB in each well and will be incubated in a shaking incubator at 180 rpm and 37Â Â°Â C in the presence of chloramphenicol and an inducer which is supplied by the manufacturer. 100 ÂµL of culture will be transferred to a regular 96-well plate and 100 ÂµL of 30 % (w/v) glycerol will be added and the plates will be stored at -70 Â°Â C (Soo et al 2010 ).
Miroarray construction and post processing : Fosmid DNA from 96 -will plates will be transformed to 384 will microplates and samples will be diluted with equal volume of 40% (v/v) DMSO and will be gently mixed with multichannel pipette. Clones containing target gene will be used as positive controls. Fosmid DNA samples and control DNAs from the 384-well microplate will be arrayed onto amine coated glass slide at 55-58% relative humdity ausing micro array arrayer. After printing, the slides will be crossed linked by UV irradiation. The slides will be exposed to 80 mJ of UV irradiation and will be washed at room temperature with 0.1 ( w/V ) SDS for 4 min, followed by washing with water for 2 min. To denature template DNA, the slides will be boiled for 10 min and will be suddenly placed in cold water. The slides will be dried by centrifugation at 950 * g for 5 min.
Fluorescent labeling of the probe :The amino acid sequences of the sixty species for the enzyme Reductive Dehalogenase were downloaded from the NCBI and multiple sequenced alignment was done. The conserved region were selected from the alignment and degenerate primers were generated. These primers will be used for the amplification of the conserved region of the Reductive Dehalogenase multiple sequence alignment. PCR will be done using these primers and PCR products will be purified using PCR purification kit. The labeling of the pcr product will be performed using Bioprime DNA labeling kit. Probe DNA will be mixed with random octamer and will be denatured by boiling. The denatured probe will be mixed with the labeling reaction solution and the reaction mixture will be incubated at 37 Â°C for 3 hr. The labeled probe will be purified using PCR purification kit.
Microarray Hybridizattion :The fluorescence labeled probe will be mixed with hybridization solution . A part of the hybridization solution mixture will be heated for 5 min at 95 Â°C using PCR machine. Denatured probe will be deposited onto the glass slide.
Image processing and data analysis :The microarray slides will be scanned using a Scan Array 4000 Microarray Analysis System at a resolution of 10 Âµm. Each spot will be quantified using Genepix software (Soo et al 2010 ).
Bioinformatics analysis: After getting the sequencing results, the Open Reading Frames responsible for the degradation of the chlorinated compounds will be identified. For the identification of ORFs the tool ORF finder will be used. After finding the ORF Blast will be done to find the similarity of the ORFs with the genes present in the databases. To know the phylogenetic distance of the ORFs discovered, Phylip will be used.
Metagenomic DNA image.
In silico pcr result
Fosmid library construction