BASIL (Biochemistry Authentic Scientific Inquiry Laboratory)

Arthur Sikora, Nova Southeastern University
Paul A. Craig, Rochester Institute of Technology
Herbert J. Bernstein, Rochester Institute of Technology
Colette Daubner, St. Mary's University
Anya Goodman, Cal Poly San Luis Obispo
Stefan M. Irby, Purdue University
Julia R. Koeppe, State University of New York at Oswego
Jeffrey L. Mills, Rochester Institute of Technology
Suzanne F. O'Handley, Rochester Institute of Technology
Michael Pikaart, Hope College
Ashley Ringer McDonald, Cal Poly San Luis Obispo
Rebecca Roberts, Ursinus College
Location: Headquartered at RIT in New York

Abstract

This curriculum from the BASIL (Biochemistry Authentic Scientific Inquiry Laboratory) biochemistry consortium aims to get students to transition from thinking like students to thinking like scientists. Students will analyze proteins with known structure but unknown function using computational analyses and wet-lab techniques. BASIL is designed for undergraduate biochemistry lab courses, but can be adapted to first year (or even high school) settings, as well as upper-level undergraduate or graduate coursework. It is targeted to students in biology, biochemistry, chemistry, or related majors. Further details about the BASIL biochemistry consortium can be found on the BASIL blog, http://basiliuse.blogspot.com/

The curriculum is flexible and can be adapted to match the available facilities, the strengths of the instructor and the learning goals of a course and institution. These lessons are often used as part of upper-level laboratory coursework with at least one semester of biochemistry as a pre-requisite or co-requisite. The lab has been designed for classes ranging from 10-24 students (working in teams of two or three) per lab section. This lesson can be adapted to laboratory courses for introductory biology, cell and molecular biology, or advanced biology labs.

Student Goals

  1. Combine information from multiple experiments to develop and test a hypothesis
  2. Understand the roles of bioinformatic data as a powerful partner to wet lab experiments
  3. Gain a deeper understanding of protein structure/function relationship

Research Goals

  1. Elucidate the specific function of putatively characterized proteins
  2. Optimize enzymatic assays for diverse enzyme classes and better understand the substrate diversity of the proteins of interest

Context

BASIL is a collaboration of faculty across the country that is always expanding to reach new students. The curriculum is aimed at upper-level students but can be easily adapted to introductory students. Our 11 modules span an entire semester but each stands alone and instructors are able to tailor experiments to fit their term. The students benefit from experience in chemistry/biology labs but such experience is not necessary.

Target Audience:Major, Upper Division
CURE Duration: A full term, Multiple terms

CURE Design

The BASIL modules together comprise a course designed to address foundational concepts and skills set forth by the Education and Professional Development committee of the American Society for Biochemistry and Molecular Biology (ASBMB). These include enzyme catalysis, macromolecular structure, and the quantitative, analytical nature of biochemistry. The overall research goals goals require students to master in vitro bench techniques such as protein expression, purification, protein concentration, SDS-PAGE, enzyme assays, and enzyme kinetics to test protein function in the lab. At the same time, this CURE integrates in silico computational methods including BLAST, Pfam, Dali, PyMOL, ProMOL, and PyRx/Autodock to analyze protein structure.


BASIL goes beyond a traditional "cookbook" style laboratory course in that the proteins students study have not been extensively characterized previously. Instead, students discover new knowledge about previously uncharacterized proteins from the Protein Structure Initiative (PSI). The PSI was a National Institute of General Medical Sciences program funded from 2000-2015 to generate a structural biology database. Over the course of its 15-year lifetime, the PSI researchers cloned, expressed, and solved X-ray crystal structures of over 4000 proteins. Of these, BASIL instructors have identified a subset of bacterial proteins that have sequence similarity to known proteins with assigned enzyme classes. Initial BASIL iterations, including the current modules, focus on enzymes with predicted similarity to hydrolysis-catalyzing enzymes. In terms of the International Union of Biochemistry and Molecular Biology nomenclature, these fall in the Enzyme Commission (EC) class EC3, or hydrolases. These were selected because, first, students have typically been previously exposed to catalytic mechanisms of several hydrolases in their biochemistry coursework, and, second, many can be conveniently assayed using chromogenic para-nitrophenol derivatives as substrates. Plasmids allowing inducible expression of these presumed hydrolases (and all other PSI proteins) and including one or more affinity purification tags are readily available. Starting with an expression plasmid, students discover optimal expression and purification strategies, assay development, and kinetic analysis, guided by the conclusions they draw from their computational work. Overall, the level of inquiry in these modules varies, starting from a low level in some of the traditional labs such as the protein concentration lab where the biggest challenge is to find the best approach and concentration ranges for standards and samples, to wide open inquiry with the computational biology tools when students identify and modify ligands in an attempt to predict a physiological substrate for their protein.

Core Competencies:
Nature of Research: Basic Research, Informatics/Computational Research, Wet Lab/Bench Research

Tasks that Align Student and Research Goals

Research Goals →
Student Goals ↓
Research Goal 1: Elucidate the specific function of putatively characterized proteins
Research Goal 2: Optimize enzymatic assays for diverse enzyme classes and better understand the substrate diversity of the proteins of interest


Student Goal 1: Combine information from multiple experiments to develop and test a hypothesis

Gather data on the known physical feature(s) and putative function(s) of the protein of interest

Analyze data from each experiment and draw conclusions about the implications for protein function

Evaluate and modify hypotheses based on data from each experiment

Analyze the scope and limitations of each technique and determine the veracity of the results generated

Propose a substrate to use for enzymatic experiments

Complete a final project that combines data from each experiment performed, highlighting the development of hypotheses

Develop protocols for new enzyme classes and associated modules as needed (projects to utilize NUDIX hydrolyses and kinases are underway)

Test novel reaction buffers and tailor reaction conditions to new enzymes

Optimize instrumentation to suit experimental products as needed



Student Goal 2: Understand the roles of bioinformatics as a powerful partner to wet lab experiments

Perform bioinformatic experiments that test for protein homology in primary structure, domain organization, 3-D structure, and active site orientation

Perform molecular docking simulations

Analyze data from multiple bioinformatic experiments to determine which data are most indicative of true protein function

Using the sum of the bioinformatic data, propose a substrate or substrates that for in vivo experiments

Troubleshoot errors that may hamper in silico experiments, utilizing novel programs or protocols as needed

Adapt bioinformatics experiments to new types of enzymes

Develop programs and protocols that are robust when employed across enzymatic classes when necessary

Troubleshoot errors that are inevitable when studying new enzymes



Student Goal 3: Gain a deeper understanding of protein structure/function relationship.

Discuss the role of amino acid position in enzymatic reactions

Analyze the connection between protein structure and function when performing bioinformatics modules

Identify the amino acid residues found in the active site

Describe the hypothesized role of the active site residues

Complete a final project that combines data from each experiment performed, highlighting the role of the 3-D shape that gives proteins function

Apply structure data from new enzyme classes to hypothesize function(s)

Propose an optimal substrate and enzymatic mechanism appropriate to the selected enzyme

Design enzymatic experiments based on structural knowledge


Instructional Materials

The BASIL project consists of 11 lab experiments that can be done in numerical order or in any order that is appropriate for the course. Experiments may be omitted completely at the instructors discretion.

All student modules are available on our git hub page https://basilbiochem.github.io/basil/.

Assessment

Each module comes with sample assessment questions that are aligned with the learning objectives. These assessments and the answers are available after registration with the project. To register, email basilbiochem@gmail.com from your university e-mail address and include your name, university affiliation, and the courses where you are considering using the BASIL curriculum. Please use the subject line BASIL Registration for your e-mail.

Instructional Staffing

The BASIL CURE does not have a set staffing guideline. Any experiments can be conducted in most academic biochemistry labs.

Author Experience

Arthur Sikora, Nova Southeastern University

The BASIL approach to teaching biochemistry was started by Paul Craig and several faculty supervising individual undergraduate research projects. In this setting, the students appeared to grow as scientists and the projects could be done in parallel with multiple students working on different proteins using similar procedures.


Advice for Implementation

BASIL is designed with flexible implementation in mind. A recent partnership with the plasmid repository DNASU a special set of BASIL plasmids is available for $25.

Instructors meet online weekly to discuss the project and any member of BASIL is happy to share their experiences with the curriculum.

Iteration

Students use each experiment as a piece of data to determine the preferred substrate of their protein of interest (POI). The bioinformatic experiments frequently provide conflicting results. Each group makes data driven decisions about the enzyme class(es) that they think best represents the unknown protein's function. Programs do not work well for all POIs and students are encouraged to explore and use tools that fit their protein.

All experiments are adaptable to failure, however, if plasmids are not transformed effectively or protein expression is poor the protein concentration, SDS-PAGE and enzyme activity experiments will not produce optimal data. Instructors are encouraged to have back up protein samples that can be used to expose studnets to these important techniques.

Using CURE Data

Successful enzymatic characterization will be published and student authors recognized. The data generated about one protein of interest can be polled from multiple campuses and/or years to fully characterize its function substrate and enzymatic properties. The BASIL group is working to finish the projects that students do not have time to complete during the course time. With the goal of presenting the work at local campuses and international meetings.

Resources

The full collection of BASIL modules is available at the link below

https://basilbiochem.github.io/basil/

BASIL publications

Irby, SM, Pelaez, NJ, Anderson, TR. Anticipated Learning Outcomes for a Biochemistry Course-based Undergraduate Research Experience Aimed at Predicting Protein Function from Structure: Implications for Assessment Design. Biochemistry and Molecular Biology Education, 46(5), 478–492 (2018)


Irby SM, Pelaez NJ, Anderson TR. How to Identify the Research Abilities That Instructors Anticipate Students Will Develop in a Biochemistry Course-Based Undergraduate Research Experience (CURE). CBE Life Sciences Education 17:es4, 1-14 (2018).


Craig PA, Anderson T, Bernstein HJ, Daubner C, Goodman A, Irby SM, Koeppe J, Mills JL, Pikaart M, Ringer McDonald A‡, O'Handley SF, Roberts R, and Stewart R. Using Protein Function Prediction to Promote Hypothesis-Driven Thinking in Undergraduate Biochemistry Education. The Chemist 91:1-8 (2018).


Craig, PA. Lessons from my undergraduate research students. Journal of Biological Chemistry, 293, 10447-10452 (2018), DOI: 10.1074/jbc.RA118.003722.


Craig, PA. A survey on faculty perspectives on the transition to a biochemistry course‐based undergraduate research experience laboratory. Biochemistry and Molecular Biology Education 45, 426-436 (2017) DOI: 10.1002/bmb.21060.

ProMOL publications

Osipovitch M, Lambrecht M, Baker C, Madha S, Mills JL, Craig PA, Bernstein HJ. Automated protein motif generation in the structure-based protein function prediction tool ProMOL, Journal of Structural and Functional Genomics 16:101-11 (2015) DOI: 10.1007/s10969-015-9199-0; PubMed PMID: 26573864. In process at NIHMS. NIHMS ID: NIHMS738909.


McKay T, Hart K, Horn A, Kessler H, Dodge G, Bardhi K, Bardhi K, Mills JL, Bernstein, HJ, Craig PA. Annotation of Proteins of Unknown Function: Initial Enzyme Results, Journal of Structural and Functional Genomics 16:43-54 (2015) DOI: 10.1007/s10969-015-9194-5; PubMed PMID: 25630330; PubMed Central PMCID: PMC4332402.


Hanson B, Westin C, Rosa M, Grier A, Osipovitch M, MacDonald ML, Dodge G, Boli, PM, Corwin CW, Kessler H, McKay T, Bernstein HJ, Craig PA. Estimation of Protein Function Using Template-Based Alignment of Enzyme Active Sites. BMC Bioinformatics, 15:87 (2014), DOI:10.1186/1471-2105-15-87; PubMed PMID: 24669788; PubMed Central PMCID: PMC4229977.


Grell L, Parkin C, Craig PA, Slatest L. EZ-Viz – A Tool for Simplifying Molecular Viewing in PyMOL, Biochemistry and Molecular Biology Education 34:402-407 (2006) DOI: 10.1002/bmb.2006.494034062672.




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