In order to develop a further understanding of the evolutionary relationships between different Chlorella algal strains and related species, methods of algal DNA extraction, PCR, sequencing, and analysis were tailored to our project. With the goal of understanding algal relationships and an intent of affecting algal biofuel production, DNA from multiple regions of algal cells was targeted. Ribosomal DNA including the 18S, ITS1, 5.8S, ITS2, and 28S regions; Chloroplastic DNA (the RuBisCO large subunit coding region); Genomic DNA (the RuBisCO small subunit coding region); and Mitochondrial DNA (Cytochrome C Oxidase subunit I coding region) were picked to be analyzed from each of our algal strains. The comparison of the phylogenetic trees is then being used to determine relationship grouping patterns with increasingly robust trees as more sequencing data is obtained. Further analysis and sequencing of the four regions should give a better understanding of relationships and help to determine the proximity of certain chlorella‐like algal species to one another. Furthermore, extended distance between two strains of the same species provides ground for questioning the nomenclature of certain strains with comparison to their actual genetic composition. Funding provided by NSF‐EPSCoR: 1004–094.
Using the 18S (partial), ITS1 (Internal Transcribed Spacer 1), 5.8S, ITS2 (Internal Transcribed Spacer 2) regions of the genomic SSU (small subunit) DNA, we are able to use basic bioinformatics tools to create an effective phylogenetic tree. Sanger sequencing produces a 1.2–1.5 kb region for each individual species that is annotated into four elements, (partial 18S, ITS1, 5.8S, and ITS2) and is formatted for stand‐alone MAFFT v6.903b (Multiple Alignment using Fast Fourier Transform). The multiple alignment is then carried out on each element and concatenated to remove the potential overlap between the elements. Stand‐alone PhyML v3.0 (Phylogenetic estimation using Maximum Likelihood) is then used on the multiple alignment data, and a tree can be viewed using FigTree v1.3.1 (a phylogenetic tree editor and viewer program). The results of this method gives well‐defined clades that are now being used in genera and even species level determination. Using our simplistic method is an effective way to engaging the problem of green algae identification.
The object of this project is to identify changes in soil microbial community DNA and Fatty Acid profiles caused by storage, using capillary electrophoresis single‐strand conformation polymorphism (CE‐SSCP) and fatty acid methyl ester (FAME) analysis.There were six different storage treatments tested (−80°C, −20°C, 4°C, freeze dried, air dried, oven dried) on soil samples collected from 4 different locations in Nebraska. Samples were taken at a depth of 0.0 cm to 5.0 cm from three biological replicates at each collection site. After collection, soils were sieved and subsamples were placed into each storage treatment for five weeks then analyzed, with the exception of one subsample (fresh) which had DNA and fatty acids extracted within 36 hours of collection. Additional fresh samples were collected and processed two weeks after initial collection and seasonally.The CE‐SSCP and FAME analysis will illustrate the microbial community and its diversity for an individual soil sample through the number of peaks, molecular size of peaks and relative peak heights. Using statistical analysis it can be determined which storage treatments altered the soil microbial community profile when compared to the fresh subsample. Results will be presented to show the effectiveness of these two methods to detect small variations in the soil microbial community. Funded by National Institute of Justice (25‐6228‐0159‐001).
As alternative fuel research continues it is important to educate students as to be an active part of the scientific community. By integrating a new and interesting research area, such as algae biofuels, with a basic concept it is possible to have more student involvement and interaction. Here we use interactive worksheets combining basic knowledge of algae, DNA, and our basic concept: phylogenetic trees. The worksheets are supported by laboratory experiments where the students extract algal DNA, amplify a specific region, obtain the sequence and then build a phylogenetic tree with their obtained sequence and other sequences provided to identify the algal species. The laboratory module is being implemented at three different universities in Nebraska: Creighton University, University of Nebraska‐Kearney, and University of Nebraska‐Lincoln. The laboratory module is set up to cover multiple skills and education requirements so that it may fit in to a multitude of classes. Currently it is being implemented in a microbiology lab course, biochemistry lab course, and cellular biology lab course. This research is funded by: NSF EPSCoR‐ 1004–094
Capillary electrophoresis can separate fragments of nucleic acids using single strand conformation polymorphism (SSCP) and terminal restriction fragment length polymorphism (T‐RFLP). These methods have been increasingly used in microbial ecology to develop fingerprints of the microbial community within soil. T‐RFLP is based on amplifying a region of DNA common to multiple species using conserved PCR primers whereas SSCP detects mutations in DNA fragments due to changes in the secondary structure of single‐stranded DNA fragments. The objective of this study is to use soil samples to compare molecular profiles generated by CE‐SSCP and T‐RFLP in detail. The soil samples will be collected from four locations representing four soil types. One set of soil subsamples will be analyzed immediately following collection and six subsamples will be placed in different storage treatments: cooling at −4C, freezing at −20C, freezing at −80C, freeze drying, air drying, and oven drying. DNA will be extracted from the samples, run through polymerase chain reaction (PCR) to amplify and fluorescently tag the genes of interest. T‐RFLP uses restriction enzyme MspI after PCR, while SSCP does not. Then, the microbial community fingerprints are analyzed. We hypothesize CE‐SSCP and T‐RFLP will generate similar fingerprints of the microbial community within soil. Supported by National Institute of Justice (25‐6228‐0159‐001).
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