Abstract: Investigating the Electron Transfer Kinetics of Eosin Y Photosensitizers Using Single Molecule Spectroscopy

This summer, my research will analyze the electron transfer kinetics of Eosin Y (EY) within the context of dye-sensitized photocatalysis technology. As climate change continues to threaten our planet, finding viable renewable energy sources becomes increasingly important, especially as the global energy demand will increase by 25% by 2040. Dye-sensitized photocatalysis (DSP) offers a promising solution to this problem by using solar energy to generate hydrogen fuel, but at the moment it is not efficient. Our research group will work to understand the underlying electron transfer processes in order to move forward with DSP. This understanding will be achieved through single-molecule spectroscopy (SMS) techniques. We will investigate EY on a titanium dioxide (TiO2) substrate, a semiconductor that allows us to understand how EY would function in a real DSP system. Furthermore, we will compare results from single molecules in the presence of oxygen to those in the absence of oxygen (nitrogen) to understand how environment affects electron transfer.

Week 1: Find where TEs are in the M. guttatus genome and generate frequency histograms for important features of DNA and LTR transposons

In the first week of my research, I started from locating the TE sequences in the Mimulus guttatus genome file which was provided by Puzey Lab. To do that, I used the program RepeatMasker. RepeatMasker is a command line program that runs in the terminal interface. It aligned the M. guttatus genome sequences with the reference genome file, which was also provided by Puzey Lab, and found the loci of TEs in the plant genome. First, I ran the program on the whole genome but it encountered an issue and failed. Then I tried to divide the plant genome into 14 separate parts and ran the program on each of them. In this way, I got the output file containing a bunch of data for each matching repeat. To narrow down to information that was useful for my research, I focused on the data of actual TEs which had two main categories, DNA transposons and LTR transposons. I extracted the percentage of insertion, deletion, and divergence of those TEs in the first piece of TE sequences named scaffold_1 using programs in python. After that, I made frequency histograms of the three percentages and the size of TEs as well for two types of TEs separately. When successfully generated the plots for scaffold_1, I scaled up to do the same thing for the whole genome. The histograms for the entire plant genome are as followed:

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