1. Bioinformatics for Biofuel Cell Development Parker Evans

2. Overview What are fuel cells? How do you make a fuel cell? Laccase Sequence Source ◦ Laccase Sequence Histogram T1 Cu Site – REDOX Potential ◦ REDOX Potential results N-Glycosylation – Secretion ◦ N-Glycosylation results Results Resources

3. What are Fuel Cells? Fuel cells simply steal electrons from biological processes Implantable sensors ◦ Glucose monitors ◦ Heart rate etc. Terawatts (10¹²W) of power + CLEAN water from wastewater

4. How do you make a fuel cell? Grow fungusFilter proteins Adsorb proteins to electrode Collect electricity! Collect additional products (ie. drinking water)

5. Laccase Sequence Source There are 2,674 fungal laccase protein sequences in the UniProt database Approximately half (50.2%) of these are protein fragments under 100kb ◦ Laccase average seq. length: 453AA  Min = 100; Max = 906 Fragments were removed using UniProt’s built in feature The remaining 1,331 sequences were run through the regex_fasta program

6. Laccase Sequence Histogram

7. T1 Cu Site – REDOX Potential REDOX potential of laccase determines the voltage of the system Pardo et al. found the REDOX potential is directly determined by the axial amino acid (AA) ◦ L = low, M= med., F = high Th Ö ny-Meyer et al. found that the T1 copper motif is highly conserved: ◦ HCHXXXHXXXXL/M/F

8. REDOX Potential 162 of 1331 sequences, 12%, contained phenylalanine axial amino acids at the T1 copper center

9. N-Glycosylation - Secretion The program Secretome.P uses the occurrence of N-Gycosylation sites to determine the probabilitity that a given protein will be secreted I used the regular expression behind their open-source program to find N- Glycosylation sites in my program ◦ N[^P](S|T)[^P]

10. N-Glycosylation Of the 162 high REDOX potential laccases, 9 contained N- Glycosylation sites Interestingly none of these sites contained serine

11. Results My motif finder pipeline narrowed the thousands of candidate organisms to less than 0.5% of the initial input while retaining the optimal features of the candidate proteins The prospective species are: ◦ Panus rudis, Moniliophthora roreri, Cerrena unicolor, Heterobasidion irregulare, Cerrena sp., Fusarium oxysporum, Spongipellis sp., Fusarium solani T. versicolor and P. ostreatus were identified as high REDOX potential laccases, but not secretors

12. Resources Reiss, R., Ihssen, J., Richter, M., Eichhorn, E., Schilling, B., & Thöny-Meyer, L. (2013). Laccase versus laccase-like multi-copper oxidase: a comparative study of similar enzymes with diverse substrate spectra. PloS one, 8(6), e65633. Pardo, I., & Camarero, S. (2015). Laccase engineering by rational and evolutionary design.Cellular and Molecular Life Sciences, 1-14. http://www.ncbi.nlm.nih.gov/CBBresearch/Spouge/htm l_ncbi/html/fasta/matchregex.html http://www.ncbi.nlm.nih.gov/CBBresearch/Spouge/htm l_ncbi/html/fasta/matchregex.html Feature based prediction of non-classical and leaderless protein secretion J. Dyrløv Bendtsen, L. Juhl Jensen, N. Blom, G. von Heijne and S. Brunak Protein Eng. Des. Sel., 17(4):349-356, 2004

13. Questions? https://github.com/evansparker/PLS-599

14. Water Analogy Voltage = electrical pressure Current = electrical flow-rate Resistance = electrical friction R R C C V