A Bioinformatic Look at Iron Uptake in Insects
Emily Ragan, Metropolitan State University of Denver
Iron is a challenging element for living organisms because iron is essential for many processes but it is also potentially toxic. The processes for storing and moving iron between cells in humans and other mammals are partially understood. However, fundamental differences exist between mammals and invertebrate animals, such as insects. Processes involved in iron uptake in insects remain unclear. The goal of this research project is to understand how iron is transported from one cell to another in insects. Our research findings may help inform studies of iron transport in mosquitos and other blood-feeding insects, who ingest large amounts of iron in a blood meal, and could contribute to the discovery of a more evolutionarily ancient iron transport mechanism in insects and other invertebrate animals. Better understanding of this key process in insect physiology may also provide a target for a novel insect control strategy. Students will use protein sequences with potential roles in iron uptake from the fruit fly, Drosophila melanogaster, to perform BLAST searches, make protein sequence alignments and identify putative orthologs. This work will extend our findings in Drosophila to other insect species and help us find new candidate genes to test for potential roles in iron uptake.
- Use common database and bioinformatics tools to explore a gene and analyze protein sequences
- Analyze data and generate novel predictions; make and defend the structure/function-related conclusions drawn from data
- Communicate about research progress, including keeping quality records during the process
- Investigate proteins involved in Drosophila iron uptake and find potential orthologs other insect species.
- Make a multiple sequence alignment of the assigned Drosophila protein and related insect proteins, then use the alignment and protein family information or a related crystal structure to identify key amino acid residues and make predictions about protein structure and function
Biochemistry II (CHE 4320) is a second semester biochemistry course required for biochemistry majors. Biochemistry I is a prerequisite, in which students were exposed to DNA structure, protein structure, and central metabolism (glycolysis through the citric acid cycle and electron transport chain) . CHE 4320 meets twice a week for 110 minutes in a lecture-style classroom for a typical 16 week semester. Many students will have an extensive biology background but will vary in the upper division courses they have completed (Cell and Molecular Biology, Genetics), while some chemistry majors may have only had Biochemistry I. This project will take place during the first third of the semester in the second half of the class period.
Student enrollment: 15-35 students
CURE Duration:Half a term
The big research question that I am working on (in collaboration with Dr. Maureen Gorman at Kansas State University) is "How does iron enter insect cells?" An even larger question is, how do insects maintain the appropriate amount of iron and avoid the problems of excess or deficiency?
This course-based research is centered around introducing students to common bioinformatics techniques used in biochemistry and related fields. Many students have access to a laptop but can also make progress by using a tablet or phone. At least one class period in the semester I schedule time in a computer lab. One challenge I continue to work on is how to tell my research story in a way that engages my students. Having testimonials from previous students and the presence of a previous student in the class through a Learning Assistant (LA) program have proven helpful.Core Competencies:Analyzing and interpreting data
Nature of Research:Informatics/Computational Research
Tasks that Align Student and Research Goals
Student Goals ↓
- Summarize the processes of transcription and translation
- Describe the differences between a gene and a mature eukaryotic mRNA
- Describe the four different levels of protein structure; explain how primary structure related to tertiary structure and protein function
- Distinguish between homologs, orthologs and paralogs
- Summarize current, general knowledge about the role of iron in insects and humans based on at least one provided review article
- Use FlyBase and bioinformatics tools to work with DNA and protein sequences
- Import FlyBase sequences into Benching to relate DNA (gene), mRNA and protein sequences
- Identify how many different isoforms of a gene (both mRNA and protein level) are present
- Describe the Drosophila life cycle
- Analyze RNAseq expression data in FLYBase and answer questions like "Are there differential levels of different mRNA isoforms at different developmental stages or cell types?
- Perform BLAST searches with a Drosophila iron-related protein to find related proteins in seven other (specified) insect species
- Analyze BLAST search results and identify best-match sequences
- Make regular, individual "notebook" entries (at least one per week spent on the project) in Benchling to track data and project progression
- Discuss the group project with group members
- Work with group members to analyze results and make sense of information and data
- Write a group memo to the professor briefly summarizing the current status of the project, including what has been completed, any challenges encountered, and how the challenges were overcome or are being addressed
- At the end of the project write a final group memo about the work to collaborator (Dr. Maureen Gorman at Kansas State University)
Schedule for CHE 4320 and Iron-uptake CURE (Microsoft Word 2007 (.docx) 139kB May3 19)
Benching Introductory User Guide for CHE 4320.docx (Microsoft Word 2007 (.docx) 79kB May2 19)
Directions for Benchling Posts (Microsoft Word 2007 (.docx) 154kB May1 19)
Day 2 CHE 4320 Spring 2019 Group 1.docx (Microsoft Word 2007 (.docx) 84kB May3 19)
Day 3 of Class & Group project Day 2 Sp 2019.docx (Microsoft Word 2007 (.docx) 68kB May3 19)
Day 4 Day 3 of project Transcripts S19.docx (Microsoft Word 2007 (.docx) 74kB May3 19)
Day 5 Analyzing RNA Seq data CHE 4320 Spring 2019 .docx (Microsoft Word 2007 (.docx) 1.4MB May3 19)
Day 7 Protein alignment Sp19.docx (Microsoft Word 2007 (.docx) 355kB May3 19)
Day 8 Chimera 3D structure.docx (Microsoft Word 2007 (.docx) 280kB May3 19)
Group Evaluation for DNA protein project.docx (Microsoft Word 2007 (.docx) 73kB May1 19)
Benchling Entry Rubric (Microsoft Word 2007 (.docx) 66kB Jun6 18)
Instructions for the Memo to Maureen.docx (Microsoft Word 2007 (.docx) 160kB May2 19)
Emily Ragan, Metropolitan State University of Denver
I want to help students apply their knowledge to a real-world question and using real-world tools while still in the supportive structure of a course so they can get support as they transfer their knowledge. I also want students to explore the ideas of "what is unknown to me" versus "what is unknown to the scientific community as a whole". Finally, I want to keep my research in my mind even while primarily focusing on teaching during the semester.
Advice for Implementation
One strength of this project is that it could be easily adapted to many different research projects, just change the proteins that you are assigning the students to work with. Students get an opportunity to use many tools; their contribution is to use structural information and information from protein sequence alignments to predict interesting structural features and key amino acid residues.
Be sure to take time to explain why this project is worth the students' time. To address why research is important, and why it is to feel confused or muddled at times, I have the students watch a Ted talk by Uri Alon. I also mention that undergraduate research is valuable for students but not all students have the time in their schedule to work on an independent project with a professor. This opportunity is designed to help them develop skills that will benefit them later in the semester and in future work. Finally, I have now been able to get testimonials from previous students, which show ways that students have actually benefited.
Benchling is a lab notebook and sequence analysis product that is free for academic use. Benchling furthers the goals of the CURE by providing a shared platform for for working with DNA and protein sequences and provides a place for student to type notes, imbed links, and otherwise track their progress. I create a project for the class and invite students to join it. Students who are not already Benchling users are invited through the Benchling program using their school email address.
Many students like making independent Benchling entries because it gives them a chance to show their progress individually, and they can also pose their own questions. One potential challenge is that some work will only be performed by one person but everyone needs to include it in their entry. I encourage students to clearly identify who did what and to write their own answers to questions. I appreciate being able to read the student responses and give guidance on the project while it is ongoing. The Benchling entries are a great opportunity for me to correct student mistakes early, so they do not cause problems later. On the more challenging side, grading the Benchling entries can be very time consuming, even for a class of just 20 students. If you have a larger class then group Benchling entries might be more useful.
All groups read a review comparing iron uptake in insects and humans (Calap-Quintana et al. 2017). Each group was assigned a protein product and its corresponding gene to explore. To better understand the protein sequence, groups were assigned to a second paper with information about that family of proteins (Ehrnstorfer et al. 2017, Xiao et al. 2014, Verelst and Asard 2003). Finally, groups were given a paper that was published with a 3D structure of the protein, which in one case was the same paper as the second paper (Ehrnstorfer et al. 2017, Zhang et al. 2018, Ganasen et al. 2018). This helped guide their investigations of the 3D structure. The alignments the students made allowed them to related the 3D structure information to their protein of interest. Highly conserved regions are likely to be similar to the 3D structure, while major sequence differences could mean different structure and function in that part of the protein. Identifying whether key important amino acid residues are conserved or not can help us reflect on potential roles and functions of the protein of interest.
In this CURE a final memo is useful because it gives me one document with all of the relevant student findings that I can refer back to later and can share with my collaborator, Dr. Maureen Gorman at Kansas State University. I have found that having the students submit a draft memo first, which I read and give feedback on, has been helpful for increasing the iterative nature of the assignment and helping students create a stronger final product. My collaborator reads the final memos and writes a memo back summarizing what was helpful to her and helping the students see the larger context of their contribution. I also read the final memos and assign the final grade.
Students learn how to perform certain types of analysis (protein BLAST, making multiple sequence alignments, analyzing a crystal structure and mapping regions back to the multiple sequence alignment). Most are performed multiple times through the project, both because of initial challenges and because they come up multiple times. For example, students can practice performing a multiple sequence alignment to compare different protein isoforms, make a multiple sequence alignment with all of the top protein BLAST hits from other insect species, and then also make an alignment between their sequence and the sequence that was used for the crystal structure.
The students make multiple Benchling entries and memo iterations, after which gives them a chance to repeat the process and make improvements after getting feedback.
While not directly related to my research, the second half of the class involves an independent paper assignment where each student analyzes a protein of their choosing. Students have a much easier time delving into the biochemical detail I want when they are using a multiple sequence alignment and focusing on specific amino acids in a 3D structure.
I have performed multiple iterations of this CURE. The detailed information provided here matches how it was taught in Spring 2019.
Using CURE Data
Thus far student data has contributed to a poster presentation at the MSU Denver undergraduate research conference (April 2019) and a poster presentation at the Arthropod Genomics Symposium (June 2019). Eventually we will get enough data that we can perform a phylogenetic analysis of a whole family of proteins in Drosophila melanogaster. In order to be an author on a potential future paper, undergraduate student authors must have contributed to data collection and analysis that is included in the manuscript. In addition, the need to have contributed to the writing and literature analysis related to their contribution. Other students or class sections will be recognized in the acknowledgements.
Alon, U. (2013). Why science demands a leap into the unknown. Retrieved May 2, 2019 from https://www.ted.com/talks/uri_alon_why_truly_innovative_science_demands_a_leap_into_the_unknown
BLAST: Basic Local Alignment Search Tool. (n.d.). Retrieved May 2, 2019, from https://blast.ncbi.nlm.nih.gov/Blast.cgi
Benchling. (n.d.). Retrieved April 29, 2019, from Benchling for Academics website: https://www.benchling.com/academic/
Calap-Quintana, P., González-Fernández, J., Sebastiá-Ortega, N., Llorens, J. V., & Moltó, M. D. (2017). Drosophila melanogaster Models of Metal-Related Human Diseases and Metal Toxicity. International Journal of Molecular Sciences, 18(7), 1456. https://doi.org/10.3390/ijms18071456
Chimera. (n.d.). Retrieved May 1, 2019, from UCSF CHIMERA an Extensible Molecular Modeling System website: https://www.cgl.ucsf.edu/chimera/
Clustal Omega. (n.d.). Retrieved April 29, 2019, from Clustal Omega Multiple Sequence Alignment Tool website: https://www.ebi.ac.uk/Tools/msa/clustalo/
Ehrnstorfer, I. A., Manatschal, C., Arnold, F. M., Laederach, J., & Dutzler, R. (2017). Structural and mechanistic basis of proton-coupled metal ion transport in the SLC11/NRAMP family. Nature Communications, 8, 14033. https://doi.org/10.1038/ncomms14033
FlyBase. (n.d.). Retrieved April 29, 2019, from A Database of Drosophila Genes & Genomes website: www.flybase.org
Ganasen, M., Togashi, H., Takeda, H., Asakura, H., Tosha, T., Yamashita, K., ... Sawai, H. (2018). Structural basis for promotion of duodenal iron absorption by enteric ferric reductase with ascorbate. Communications Biology, 1(1), 120. https://doi.org/10.1038/s42003-018-0121-8
Hall, B. G. (2013). Building Phylogenetic Trees from Molecular Data with MEGA. Molecular Biology and Evolution, 30(5), 1229–1235. https://doi.org/10.1093/molbev/mst012
modENCODE. (n.d.). Retrieved May 1, 2019, from Model Organism Encyclopedia of DNA Elements - Educational Supplement website: http://modencode.sciencemag.org
Pfam. (n.d.). Retrieved April 29, 2019, from Pfam 32.0 website: https://pfam.xfam.org/
RCSB PDB: Homepage. (n.d.). Retrieved May 2, 2019, from http://www.rcsb.org/
Tang, X., & Zhou, B. (2013). Iron homeostasis in insects: Insights from Drosophila studies. IUBMB Life, 65(10), 863–872. https://doi.org/10.1002/iub.1211
UniProt. (n.d.). Retrieved April 29, 2019, from A comprehensive, high-quality and freely accessible resource of protein sequence and functional information. website: https://www.uniprot.org/
Verelst, W., & Asard, H. (2003). A Phylogenetic Study of Cytochrome B561 Proteins. Genome Biology, 4(6), R38. https://doi.org/10.1186/gb-2003-4-6-r38
Xiao, G., Wan, Z., Fan, Q., Tang, X., & Zhou, B. (2014). The metal transporter ZIP13 supplies iron into the secretory pathway in Drosophila melanogaster. ELife, 3, e03191. https://doi.org/10.7554/eLife.03191
Zhang, T., Liu, J., Fellner, M., Zhang, C., Sui, D., & Hu, J. (2017). Crystal structures of a ZIP zinc transporter reveal a binuclear metal center in the transport pathway. Science Advances, 3(8), e1700344. https://doi.org/10.1126/sciadv.1700344