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Campus Box 1137, Department of Biology, Washington University, St. Louis, MO 63130
Submitted July 1, 2004; Revised November 4, 2004; Accepted March 11, 2005
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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Key Words: undergraduate • bioinformatics • protein structure • genetic disease
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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Computer use is a fact of life for all modern life scientists. Exposure during the early years of their undergraduate careers will help life science students use current computer methods and learn how to exploit emerging computer technologies as they arise... Becoming fully conversant with databases such as the National Center for Biotechnology Information (NCBI) is important for all biology majors (NRC, 2002, 47).
Incorporating bioinformatics into undergraduate biology curriculum has been a focus of several innovative projects that have recently been described in the literature (Campbell, 2003; Centeno et al., 2003; Cooper, 2001; Feig and Jabri, 2002; Honts, 2003; Jungck and Donovan, 2000). In order to reach all biology majors, the curriculum project described here introduces bioinformatics tools and databases in a broad manner in a laboratory that accompanies a large introductory biology course. Students are then offered the option to use these tools more extensively in several smaller, upper-level courses.
This curriculum was designed to incorporate elements of inquiry, while still being compatible with a large course size and limited lab time. The lab described here requires five weekly sessions of 2 h each. Our goal was to provide a laboratory experience in which students approach problems, seek information, synthesize findings, and share results as do active scientists (NRC, 1999, 2000). In particular, we wanted to incorporate evidence-based hypothesis testing, use of primary literature sources, and communication of research results in oral and written reports.
To help students develop a sense of ownership toward their work, individualized projects were developed. The projects provided an opportunity for students to work semi-independently on their own Web-based research. The projects emphasize the link between gene sequence, protein sequence, and gene function in genetic disease. Each project was developed around a single protein with an amino acid substitution that has been linked to a genetic disease. Students begin by reading literature related to their project, then learn more about their protein using NCBI's database, LocusLink (Pruitt and Maglott, 2001), and ExPASy's database, SwissProt (Boeckmann et al., 2003). Students are then guided through a BLAST search to identify homologous proteins, a ClustalW alignment to align the homologous proteins and identify the mutation, and secondary structure prediction of their protein sequence using PSIPRED. Students perform a structure analysis of their protein and model the mutation using the program DeepView, available through the ExPASy Web site. As a result of this analysis, students are asked to predict the effect of the mutation on protein structure and function. Finally, students use the OMIM and KEGG databases to relate their protein's function to human physiology and disease states. A summary of the tools and databases used in the course is provided in Table 1. On the last day of lab, students report their results and defend their predictions in small peer groups. Students within a lab section of 20 are encouraged to serve as support for each other, facilitating group interactions within the framework of a large lecture course.
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In designing the individual projects (summarized in Table 2), each protein of focus had a single amino acid substitution that had been linked to a human disease, documented in the OMIM database, and had a published crystal structure available of either the exact protein or a close homolog. Ten projects were developed that met these criteria, and we plan to add more in the future. The materials developed for this course are publicly available online (Bednarski et al., 2004), and we hope they will be useful to others in designing bioinformatics labs.
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Context for the Course
The introductory biology core at Washington University (WU) in St. Louis is
a three-semester curriculum, Principles of Biology I, II, and III. In the
first semester, biological macromolecules (in particular DNA, RNA, and
proteins) are introduced in the context of cell biology and microbial
genetics. In the second semester, students explore eukaryotic genetics,
chromosomes, population genetics, and natural selection. In the third
semester, Principles of Biology III, students study protein
structure/function, metabolic processes, and human physiology. Principles of
Biology I and II are both taught with a weekly 3-h wet lab where students
perform experiments in molecular biology and genetics.
Students are required to have taken at least one semester of General Chemistry before enrolling in Principles of Biology I. By the time students are taking Principles of Biology III, they have taken Organic Chemistry I, and they are usually taking Organic Chemistry II concurrently. This allows biochemical principles to be introduced at a fairly advanced level in Principles of Biology III, and the textbook for the biochemistry topics in the course is Berg, Tymoczko, and Stryer's Biochemistry (2002).
The bioinformatics lab described here accompanies the third-semester course, Principles of Biology III. Care has been taken to align the laboratory projects with the proteins and metabolic processes that are discussed in the lecture portion of the course. Lectures for Principles of Biology III include topics relevant to bioinformatics such as protein evolution, multiple sequence alignments, and BLAST algorithms.
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LABORATORY DESIGN |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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Projects
The 10 projects were grouped with two projects per disease category (as
shown in Table 2). These
disease categories were used in forming small groups on the last day of lab
for students to present their oral reports to each other. These groupings
worked well, because projects in the same disease category required similar
background reading, and these readings provided some common ground for the
presentations. As previously described, each project was formulated using a
gene that was known to have a single missense mutation, resulting in a changed
amino acid in the protein sequence linked to a disease state in the literature
(OMIM database). This model of genetic disease is not generally applicable
(since most genetic problems are multifactorial), but it lends itself well to
focusing on the role of protein structure in gene function and in providing a
format for using the Web-based tools and databases. Students were introduced
to more complex models of genetic disease, such as that applicable to
atherosclerosis, during the lectures in population genetics given in
Principles of Biology II. A review of the structural basis of inherited
disease was recently published and contains several additional examples for
projects that could be developed for this laboratory
(Steward et al.,
2003).
Web Site and Materials
A Web site has been designed to provide a source of materials for the
laboratory as well as to provide links to the Web addresses that the students
commonly use in the lab. All the lab materials are available to download from
the Web site including a general laboratory manual, which includes the
syllabus, a glossary, and tutorials on the programs and databases common to
all of the projects. The glossary is designed to include the content and
terminology needed in the lab, regardless of the specific project.
The Web site also contains a separate page for each of the 10 projects where the students can download their project manual, starting DNA sequences, and any articles they are assigned to read. The project manuals contain a short introduction, reading assignments, and guide sheets specific to each project. The reading assignments include short sections from the textbook (Berg et al., 2002), a review article about the disease their protein is related to, and an excerpt from the article that described the crystal structure they will be analyzing. The guide sheets contain instructions and questions specific to each project and the database or program in use. These guide sheets are designed to be very detailed, so that students can easily use the databases and tools with minimum frustration. Although this approach does not encourage a lot of trial and error, it allows students to work at their own pace and to approach the work without anxiety.
In summary, the Web site gives students access to all the lab materials from their home computers as well as other campus computers. While lab time is usually sufficient, students can finish their work outside of class if needed.
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IMPLEMENTATION |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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In the laboratory component of the course, each session begins with a brief review of the topics from lecture that are important for the focus of that day's activities and a demonstration lasting approximately 30 min to show the basics about the Web sites and programs the students are using that day. During the rest of the laboratory session, the students work at their own speed using the guide sheets, with the instructor, the teaching assistant, and other students available for assistance.
Laboratory
In the laboratory, students use a variety of bioinformatics tools and
databases. This curriculum emphasizes availability and familiarity of
resources, which is consistent with our first goal. To begin each project,
students download a cDNA sequence from the lab Web site for a human gene
containing a single nonsynonymous mutation. Through their guide sheets,
students are instructed to first translate their sequence using a tool on the
Sequence Manipulation Suite. Next, students perform a BLAST search
(Altschul et al.,
1997) with the wild-type human protein sequence to obtain a group
of diverse, yet homologous, sequences. Students are instructed to select five
sequences, each from a different organism, from the BLAST results. They are
asked to include sequences with a range of E-values, so that the selected
sequences will be similar, but not almost identical, to their search sequence.
To accomplish this, students select sequences with E-values ranging from
10-25 to 10-75. Students then create a document
including the homologous sequences, the wild-type sequence, and their mutant
sequence in FASTA format, which they load into ClustalW
(Thompson et al.,
1994) to obtain a multiple sequence alignment. Students use this
alignment to identify the mutation and to observe regions of high and low
conservation. Next the students use the secondary structure prediction program
PSIPRED (McGuffin et al.,
2000) to identify and map secondary structure predictions onto
their multiple sequence alignment. The aim of this activity is to encourage
students to think about the three-dimensional protein structure and provide an
opportunity for students to check the prediction method. Students compare the
results of the secondary structure predictions with the crystal structure data
and generally find some disagreement, although the predictions are very close.
This activity helps emphasize the difference between predictions using
bioinformatics programs and experimental data obtained from a database.
Before students begin working with the crystal structure data, they download the pdb file for either the human protein or a homologous protein from the Protein Data Bank (Berman et al., 2000). Students then view the crystal structure using DeepView (Guex and Peitsch, 1997). In viewing the structure, students are asked to develop a hypothesis for the role of the wild-type amino acid residue and the effect the mutated residue might have on protein structure and/or function. To accomplish this, students study changes in the noncovalent interactions of the amino acid side chain when the residue is mutated. The main focus of this portion of the lab is to examine the ball-and-stick view of the side chain where the missense mutation occurs and predict noncovalent interactions of the side chain based on its chemical nature and the distance of the neighboring atoms. Examination of noncovalent interactions gives the students a chance to investigate a portion of the crystal structure in depth. The students then use DeepView to "mutate" the selected side chain to the missense mutation they are studying, examine the possible effects of the change on the local noncovalent interactions, and predict how such interactions might be maintained or changed. This activity helps reinforce the concept of non-covalent interactions in a protein structure as well as the different chemical properties of the amino acid side chains. In combination with the structure analysis using DeepView, the students are asked to draw a noncovalent interaction with the residue using Fisher projections to represent the amino acid side chains. This type of activity has been shown to help students interpret three-dimensional structures (Richardson and Richardson, 2002). Additional examples of curriculum developed to aid students in analyzing crystal structures have recently been described in the literature (Centeno et al., 2003; Feig and Jabri, 2002; Honey and Cox, 2003; Richardson and Richardson, 2002).
After studying the structure, students analyze the metabolic pathway(s) containing their protein using the KEGG database. At this point, students can examine their hypothesis regarding the change in protein function and the effect on downstream events in the pathway. Finally, students develop the link between the gene they are studying and human disease using the OMIM database (NCBI, 2000). With the "Allelic Variants" portion of the OMIM entries, the students can read about the specific mutation they are examining and compare their hypothesis with the clinical (and sometimes biochemical) data available. Finally, students organize their results into a report that contains a one-page written summary, their multiple sequence alignment, and figures created using DeepView. By the completion of each project, students have traveled from genotype to phenotype, beginning with a DNA sequence and ending with clinical data.
During the last lab session, the students meet in small groups and present their projects to each other in the form of an oral report. For these presentations, the students who are working on the same project present together to the other pair who are working on the other project in the same disease category. For example, in the Lung Cancer group, the two students working on the K-Ras project present to the two students working on the Cytochrome P450 project (see Table 2). To help ensure that students understand the presentations and the relationship between the two projects, they work together to provide answers to a group quiz about the two projects. This quiz involves four essay questions (see Table 3) that help generate a discussion about the presentations and the hypotheses that the students develop for their projects.
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An Emphasis on Providing an Inquiry-Based Experience
The parts of the curriculum that emphasize inquiry are in analyzing the
protein structure, developing a hypothesis about the structure, and writing
and discussing the report summaries. In analyzing the protein structure,
students are asked to assess the impact of the missense mutation on the
protein structure, then relate this impact to effects on protein activity.
With this activity, we are asking students to perform the first step in
laboratory mutagenesis studies, predicting the experimental outcome of the
mutation before the experiment has been performed. For most of the student
projects, the mutagenesis experiment has not yet been performed, so the
students are not able to look at experimental results of the mutations. In the
cases where the mutagenesis results are available, such as with the
phenylalanine hydroxylase project, the students read about the results and
often discover that the results are not as straightforward as their
predictions. For example, in the case of phenylalanine hydroxylase, the
students discover that many mutations lead to folding and stability problems.
The hypotheses that the students develop concerning the consequences of the
mutation are graded on the basis of how well the students explain their
reasoning and how well they incorporate the chemical concepts. Students often
develop different hypotheses than their partners who are working on the same
project, yet both can receive full credit.
After students read about the consequences of the mutation they are studying under the "Allelic Variants" section of the OMIM database and the KEGG database, they are asked to develop a conclusion for their final report that ties together all that they have learned about the mutation they are studying. As part of this conclusion, they are asked to hypothesize how the change in amino acid could lead to a symptom of a disease. Since students often develop different hypotheses to explain the same data, these differences lead to lively discussions and debates during their oral presentations. This activity helps to emphasize the importance of sharing ideas in the process of scientific research.
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ASSESSMENT TOOLS |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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To address the first aspect of the assessment, a multiple-choice test was given before and after the lab. The questions were based on information that was available in the glossary designed for the lab, although students were expected to have learned these topics through the process of their Web-based research projects. The second aspect of the assessment was addressed by a questionnaire designed to obtain students' opinions by ranking their level of agreement to a series of statements. This questionnaire also solicited comments from students on any subject related to the lab. As both of these tools were available online and class time was provided to complete the forms, both tools had a high response rate, and many comments were obtained.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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Postquestionnaire and Comments
Statements on the postquestionnaire were designed to obtain students'
perceptions of their own learning and their views on the curriculum materials,
instruction, project assignment, and overall usefulness of the lab. The
students were asked to respond to the statements using the Likert scale
(Anderson et al.,
1983; Likert,
1932). This scale and the results of the survey are summarized in
Table 5.
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The postquestionnaire is available online from the laboratory Web site (Bednarski et al., 2004), and the students completed the questionnaire during class on the day of the final presentations after completing the posttest. The questionnaires were anonymous and included an option to provide additional comments about the laboratory. Two hundred twenty-nine students out of 246 enrolled students completed the questionnaire, and 137 students chose to write additional comments. In analyzing the comments, we found that many students chose to make similar statements, and that the comments could be summarized by grouping them into categories. This grouping provides a quantitative view of the comments (see Table 6) (Wolcott, 2001).
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Assessment of Goals
The major goals we had for the lab were to introduce all biology students
to bioinformatics tools and databases, so that they had a basic knowledge of
the types of databases and tools commonly used in biomedical research.
Additionally, we wanted to create an inquiry-based lab experience for a large
course by providing independent projects, requiring evidence-based
predictions, encouraging a collaborative atmosphere, and requiring students to
communicate their results.
In regards to our first goal, the pre/posttest results show that students gained a general understanding of bioinformatics terms, as well as the tools and databases used in the lab (Table 4 and Appendix A). On the questionnaire, students also agreed that they had learned how to access and use these tools. They responded with an average of 4.0 ± 0.9 (indicating agreement on a scale of 1-5) to six different questions on the postquestionnaire assessing their comfort in using the tools and databases. In addition, 31 students chose to comment that they were now confident that they could use the bioinformatics tools on their own (Table 6). The students were slightly less confident that they would use these tools in the future; they responded with an average of 3.6 ± 1.2 that they would use the NCBI Web site (including OMIM, LocusLink, and PubMed) in the future and an average of 3.8 ± 1.1 that they would use any of the skills learned in this laboratory in the future. However, 19 students commented directly that they could see themselves using these tools in the future (Table 6). As students encounter these tools in upper-level courses and undergraduate research experiences, we anticipate that student expectations will shift.
Our second goal was most directly addressed by the comments submitted by students. In Table 6, the first three categories of comments, totaling 44 comments, focused on gaining a better understanding of what scientists do and enjoyment of the investigative nature of the projects. Since the inquiry-based approach encourages students to mimic scientists, these comments suggest that this curriculum was successful in providing that experience for many students in the course. By providing independent projects, we hoped students would develop a sense of ownership toward their research; responses to the postquestionnaire and submitted comments suggest that the majority of students enjoyed working on their own projects. In the postquestionnaire, students disagreed with statements that everyone should work on the same project (2.0 ± 0.9), indicating that most students liked the current structure of the laboratory with respect to having their own project to work on. In order to encourage students to read journal articles, we included reading assignments from primary literature sources (the crystal structure paper and several abstracts) and a review article on the disease under study. The assessment results showed that the students slightly preferred the journal articles to the textbook readings. On the questionnaire, students agreed with statements about the helpfulness of the textbook reading assignments with an average of 3.3 ± 1.2 while reporting an understanding of the journal articles with an average of 4.0 ± 0.9. These results suggest that students enjoyed the challenge of reading journal articles. Instructors also noted students commented that they particularly appreciated the introduction to the PubMed database for finding journal articles.
Although we gave students individual projects, we encouraged a collaborative atmosphere in the lab, and students often worked closely with another student nearby. The students also worked in small groups in order to present their research results and work on a joint quiz. In response to these activities, students disagreed with the statement that they would rather work more independently (2.1 ± 1.1). In Table 6, seven comments fit into the category of "Enjoyed partner and group work." Some comments further stated that the discussions with the group were important to understanding the projects. We interpreted these results to mean that most students enjoyed the collaborative experiences in the laboratory, which would not be possible if students worked completely independently on their projects.
Additional Observations
We observed that there were two areas where students commonly had
difficulties in working through their projects. First, students often had a
hard time understanding the importance of including sequences of proteins from
distantly related species in their sequence alignment, and then interpreting
their alignment once they had obtained it. Because of this, we plan to add an
activity where students will need to predict which residues are important to
protein function based on two different alignments. The first alignment will
contain protein sequences from six closely related species, and the second
will contain protein sequences from six distantly related species.
The second common difficulty was with predicting hydrogen bonds between amino acid side chains while studying the protein structure. Since many crystal structures are not solved to a resolution that can determine the location of hydrogen atoms, students were required to predict which acidic and basic residues would be protonated in order to predict hydrogen bonding. To help them prepare, we will be including a new written activity with amino acid representations created in DeepView to give students some experience with drawing hydrogen bonds between two residues before they work with the protein structures.
By observing the final presentations and talking with the students, it was clear that the preparation for the report and oral presentation was important for helping students assimilate the information that they had been collecting from the various bioinformatics databases and programs. Students became more motivated to understand the big picture in the Web-based research they were conducting when they needed to explain it to others. In the future, it may be beneficial to encourage students to begin preparing earlier in the course for their presentations to help them make important connections as they work through their projects. The main feature of understanding the big picture is understanding how genotype relates to phenotype. In fact, several students commented on the postquestionnaire that they enjoyed making the connections between DNA sequence, protein sequence, and phenotype as they worked through their projects (Table 6).
The group quizzes given after the oral presentations generated significant discussion within the groups and were important in helping the students understand each other's work. These discussions were often lively, while students fought to defend their own ideas. The presentations were kept informal to encourage discussion, but they gave students an opportunity to use scientific language that was new to them. Figure 3 shows several groups while they were presenting their final reports to each other.
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Although the curriculum is written so that most students could complete the projects working on their own time, our observations and student comments suggest that the collaboration with partners, aid from instructors, and the group work were important in helping students to avoid simple but frustrating problems, to understand the exploratory nature of their projects, and to develop their hypotheses.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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In regards to our first goal, the pre/posttest and questionnaire results showed that students learned about accessing and using a variety of Web-based tools and databases. This curriculum allows students to develop a foundation of bioinformatics skills that they will be able to build on in upper-level courses. There are several small, upper-level biology courses at WU that provide additional opportunities for students to work on bioinformatics-based projects.
It is too soon to determine the impact of this lab on the upper-level courses, since this lab was taught for the first time in Spring 2004 to sophomores, and students have 2 yr more to complete upper-level biology courses. It will be interesting to monitor both enrollment and student performance in these courses. Faculty of these upper-level courses have indicated that they found the topics covered in this curriculum to be relevant to the bioinformatics projects in their courses, and that they expect students to perform better on these projects. It appears likely that this will enable us to add additional projects to the upper-level curriculum in the future.
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ACCESSING MATERIALS |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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APPENDIX A |
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address correspondence to: April E. Bednarski (aprilb{at}biology2.wustl.edu).
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TOPABSTRACTINTRODUCTIONLABORATORY DESIGNIMPLEMENTATIONASSESSMENT TOOLSRESULTS AND DISCUSSIONCONCLUSIONSACCESSING MATERIALSAPPENDIX AREFERENCES |
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