2010 Attendee Presentations

 

Team Leader: Stephanie Lammlein

 

Collaborators:  S. Lammlein, Rootstown High School, OH; J. Klein, Northwestern College, MN; D. Biesboer, University of Minnesota, MN; T.R. Muth, Brooklyn College, NY; W. Trzyna, Marshall University, WV; M. Larkin, Queens University, Belfast, UK

 

Target Audience: High school students, high school teachers, and beginning to advanced college undergraduates, depending upon need at the consortium institutions.

Learning Goals: Introduction for students, especially beginning students, to the tools of bioinformatics, to the sampling of microbial diversity in the environment, and to allow student-centered sharing of data across multiple sites in the U.S. and the U.K.

 

Abstract: Use of freshwater resources has been growing at more than twice the rate of global population increase for the last century with clean ground and surface water becoming a diminishing resource. Raising student awareness of the issues surrounding the use of water is an important one, and in response, a consortium of institutions was formed to study microorganisms in water on a local scale using a metagenomics approach. Undergraduate and high school students will learn sampling of water, isolation of DNA, and using 16s rRNA and the tools of bioinformatics, assess the microbial diversity, microbial community composition and contamination of surface waters by pathogens. A common set of protocols is being developed to ensure that each participating institution collects data in the same manner. DNA extracted locally will be pooled for single batch PCR and sequencing at a single site. A practice laboratory is being developed to allow students to learn all aspects of bioinformatics prior to using their own data. A sequence database storing all sequences from each institution is being developed to allow students to see and analyze data from all members of the consortium. The consortium was formed to combine limited resources across institutions, and to take advantage of varied faculty expertise and different geographical locations. Aspects of this training will be integrated into a variety of courses and levels depending upon the needs of the various institutions. The consortium has representative institutions (including universities, colleges and a high school) in Ohio, Minnesota, New York, West Virginia, and Northern Ireland, UK. 

 

Team Leader: Bethany Bowling, Northern Kentucky University

 

Collaborators: Brett Couch, University of Minnesota Twin Cities

 

Target Audience: Introductory Biology Students (majors or non-majors)

 

Learning Goals:

1. Exploration and application of basic biology concepts in: genetics, molecular biology, ecology and systematics

2. Students actively and productively participate in a faculty directed research project

3. Students use evidence from bioinformatic analyses to annotate clones from the Mississippi Metagenome Project or other available data

4. Students share, question and critique analyses and annotations

5. Students generate testable hypotheses based on bioinformatic analyses

 

Abstract:  This course activity involves students using their knowledge of molecular biology and bioinformatic tools to annotate a fragment of data from a metagenomic project.  The data will originate from clones sequenced as part of a metagenomic project, such as the Minnesota Mississippi Metagenome Project (M3P).  The students will work in groups of 2-3 and will be assigned a 2-3kb fragment to annotate.  The students are informed of some basic bioinformatic tools from NCBI and JGI, such as Open Reading Frame (ORF) Finder and BLAST, and are after initial exploration are taught about more sophisticated tools such as InterPro Scan, Pfam, and others.  Students build a case for the identity of their putative genes as they collect supporting data.   

 

Alison Hill (Duke University) and Hafizah Chenia (University of KwaZulu-Natal) 

 

Team Leader: Ruth A. Gyure

 

Collaborators: Nighat Kokan (Cardinal Stritch University); Todd Nickle (Mount Royal University); Ruth A. Gyure (Western Connecticut State University)

 

Target Audience: Introductory Microbiology or Biology, Undergraduate

 

Learning Goals:

Students will learn how to use some selected bioinformatics tools

Students will get practice in testing two competing hypotheses, gatherint, and interpreting data using bioinformatics tools

Students will gain an understanding of the role of lateral gene transfer vs. simple mutation in natural selection

 

Abstract:  The target group is freshman or junior undergraduates -often nursing students- who are interested in introductory biology or health sciences.  Students will gain an appreciation and practice in scientific investigation using a defined task:  to identify if pathogenesis of a newsworthy strain of E. coli is due to mutation or horizontal gene transfer.  E. coli O157:H7 is responsible for several illnessess reported in the news.  Students have to do a little detective work to identify the name of the toxin protein (which turns out to be two subunits) and then use bioinformatics to investigate whether this is a mutation or if it's due to the introduction of a new gene - and where it came from.

 

Team Leader: Benita Brink (Adams State College)

 

Collaborators: Steven Roof (Fairmont State University) and Komal Vig (Alabama State University)

 

Target Audience: Introductory Biology students, both majors and non-majors

 

Learning Goals:

After completion of this exercise, students will be able to:

Explain how similarity is used to perform a BLAST search

Explain the BLAST search algorithm

Calculate amino acid similarity scores using various matrices

Evaluate the results of a BLAST search

Create a tree and compare it to trees found in introductory text books

 

Abstract: Students will initially be introduced to the concept of similarity by exploring an everyday example (e.g., plagiarism).They will then relate this to the similarity of amino acid sequences and the use of common matrices to quantify similarity. Students will be introduced to the alignment of sequences using BLAST and how the information gained can be used to study evolutionary relationships. The exercise will also include a reconstruction of the typical "tree of life" using a common protein sequence. 

 

Team Leader: James Moran, Mount Saint Mary College, NY

 

Collaborators: Kathryn Dye, Mount Saint Mary’s University, MD; Suzanne Lindley, Limestone College, SC

 

Target Audience: Freshman introductory Biology course

 

Learning Goals:

1.      Provide a rationale for using various bioinformatics tools to analyze an unknown sequence.

2.      Demonstrate the use of bioinformatics tools to ask biological questions.

3.      Describe the relationships among primary, secondary, tertiary structures in proteins.

4.      Describe the importance of conserved amino acids in determining protein structure/function.

5.      Explain how variations among non-conserved amino acids contribute to diversity within a protein superfamily.

6.      Describe how sequence diversification among species can reveal evolutionary relationships.

 

Abstract:  The immunoglobulin superfamily is a large group of proteins that share structural homology within one or more immunoglobulin-like domains. Beta-2 microglobulin is a single domain member of this family. In this module students are given an amino acid sequence and asked to deduce the structure or function of the protein based on visual inspection of the sequence alone. Following an introduction to the BLAST alignment tool students identify their query sequence as human Beta-2 microglobulin and discuss the importance of sequence databases and bioinformatics tools for molecular research.  Students utilize additional sequence analysis tools to predict secondary structures, determine taxonomic relationships among species and define conserved amino acids that are critical for maintaining the structural integrity of the immunoglobulin-like domain. This introductory module will be expanded for use in other courses including genetics, evolution and immunology.