Characterising the prokaryotic ATPase-ome

Alice Robson, University of Bristol

Location: Bristol, UK

Abstract

Students work in teams of 3-4 trying to identify and characterise putative ATPase enzymes from prokaryotic organisms. Each student identifies a putative uncharacterised ATPase gene from a range of prokaryotes (archaea and bacteria), and uses bioinformatic methods to characterise the gene. They then work in teams in the lab to clone, express and purify their chosen proteins; finally they characterise the protein using spectrophotometric ATPase assays. The team presents a poster on their work, then each student individually writes a report in the style of a short paper. The student grade is based on three assessed pieces: the lab book (20%), poster presentation (10%, graded as a team), and the report (70%). This course is compulsory for year 3 of our MSci Biochemistry programme, and counts for 20 credit points (out of 120 for the year). The course has been running since 2017 with an intake of 20-30 students per year, all of whom have passed the course.

Student Goals

  1. Develop independent, team working and problem solving skills
  2. Develop the ability to collect, analyse and interpret data
  3. Gain skills in recording and presenting scientific data in a variety of different forms

Research Goals

  1. Identify putative ATPase genes of interest from prokaryotic genomes and characterise them bioinformatically
  2. Characterise putative ATPases in the lab to determine novel function and/or structure

Context

This CURE was designed to be taken by students in their third year of our MSci in Biochemistry at the University of Bristol. The cohort is around 20-30 students. The course runs over two terms, with the bioinformatics taking place in autumn and the lab work in the spring (although this could all be completed in one term, if timetabling allowed). The bioinformatics takes place over 2-3 weeks and the lab work consists of 4 weeks (working 3.5 days a week to allow for lectures).

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

CURE Design

The course is based on characterising novel ATPase enzymes with a range of potential functions. Each students works on an individual gene that they have chosen, ensuring that all students must partake in both the bioinformatics and lab work, and giving a sense of ownership to their project. However, they work together in teams which allows them to support and help each other during the project. This also allows for redundancy so that if one student's project proves intractable they can join the project of another. In the unlikely event that all of the proteins chosen by the group are intractable, we supply an example protein known to express well so they can collect data and achieve the learning objectives.

The research question aligns closely to research by various members of our faculty and therefore has potential to produce meaningful data that can be taken forward within the department. A list of successfully cloned and characterised proteins is maintained and available to faculty members, and the most successful projects may be taken forward for further work within our research laboratories.

Core Competencies: Analyzing and interpreting data, Asking questions (for science) and defining problems (for engineering), Constructing explanations (for science) and designing solutions (for engineering), Planning and carrying out investigations
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: Identify putative ATPase genes of interest from prokaryotic genomes and characterise them bioinformatically
Research Goal 2: Characterise putative ATPases in the lab to determine novel function and/or structure


Student Goal 1: Develop independent, team working and problem solving skills

Students work both individually and in a team to identify and characterise a gene of interest in silico.

Students work in teams in the lab to clone, express, purify and characterise their chosen protein



Student Goal 2: Develop the ability to collect, analyse and interpret data

Students perform bioinformatic characterisation of their gene and analyse and interpret the data.

Students collect, analyse and interpret data on their protein in the lab.



Student Goal 3: Gain skills in recording and presenting scientific data in a variety of different forms

Students report the results of their bioinformatic analysis as a team poster, and an individual report.

Students keep a detailed lab book and present their findings as a poster and a report.


Instructional Materials

Students search for putative, uncharacterised ATPases within a limited list of prokaryotic genomes using sequence motifs using ProSite, or by homology with genes of interest using BLASTP or BackPhyre. They characterise their chosen gene using ProSite and perform multiple sequence alignments to identify conserved regions such as Walker A/B motifs. They perform structural predictions using JPred and Phyre (here success is dependent on the existence of close homologues in the PDB). Having identified an interesting target the students design primers for cloning.
In the lab the students attempt to clone their gene into pOPINF expression vector using InFusion ligation-independent cloning (following commercial protocols). They express the proteins in BL21(DE3) E. coli cells, or variants such as Rosetta, pLysS or Origami cells if expression proves difficult. Proteins are extracted and purified using spin nickel-affinity columns, as the expression vector adds a N-terminal histidine tag. Expression and purification is monitored using SDS-PAGE and successfully produced protein is dialysed into a storage buffer. Purified protein is quantified spectrophotometrically and ATPase activity measured using pyruvate kinase/lactate dehydrogenase linked assay.

Assessment

Assessment of student learning is through three pieces of assessed work:

1. Students submit their lab book (20% of the grade)

2. Teams present a poster (10% of the grade; team mark)

3. Students write an individual report in the style of a short paper (5000 words; 70% of the grade)

Each assignment is marked by two members of academic staff, using specific marking rubrics.

Instructional Staffing

Three faculty members are the main staff involved in teaching on the course. They deliver a short series of lectures to introduce the project and run workshops on bioinformatics, data analysis and presentation. In addition, a demonstrator (graduate teaching assistant) is present for some of the lab time, giving additional practical support to students.

Author Experience

Alice Robson, University of Bristol

I was tasked with designing a course for our third year students to develop their research skills and prepare them for an extended research project in their fourth year. We realised we could base the course on an authentic research question that was linked to research being undertaken by colleagues in my department. This would lead to a win-win situation where we create useful scientific data that could feed into our ongoing research, whilst giving students an authentic research experience which helps them develop their scientific efficacy and research skills.


Advice for Implementation

Even using tried-and-tested methods, it is essential to optimise and troubleshoot the protocols before students start in the lab. We did this by co-creation with students, employing two undergraduates to work over the summer on developing and testing protocols. We also made various instructional videos which are hosted on our virtual learning environment, which the students find very useful.

In our first iteration of the CURE there was not enough built in support for data analysis and presentation so the students struggled with writing the posters and reports. We subsequently added more workshops to develop skills required in a more structured way.

There was a significant cost associated with equipping the lab for the project (e.g. shaking incubators, centrifuges, PCR machines). Time should be built in for securing the funding for this (as well as the money to pay our undergraduate developers).

Iteration

Troubleshooting and iteration are essential throughout the lab work; complete success is highly unlikely at the first attempt of the protocols. Students have to optimise conditions for PCR, as well as for protein expression and purification, making modifications to the protocols. Troubleshooting suggestions are given in the protocols, but students often have to seek solutions online or through published protocols or manufacturers' guides. The ATPase assays in particular must be adapted and modified for the individual protein studied, meaning the students must plan and design their experiments carefully to achieve success.

Redundancy is built into the research design since students work in teams of 3-4, so the chances of success with at least one of their chosen targets is high. In the unlikely event that all of the proteins chosen by the group are intractable, we supply an example protein known to express well so they can collect data and achieve the learning goals.

Using CURE Data

A database is maintained of the genes chosen by the students each year, and the success of each project. Successfully purified proteins may be taken forward for further study in the research labs, for example for crystallisation trials for structure determination. Students will be attributed as authors of any resulting publications.

Resources

1 Berrow, N. S. et al. A versatile ligation-independent cloning method suitable for high-throughput expression screening applications. Nucleic Acids Res 35, e45, doi:10.1093/nar/gkm047 (2007).
2 Leipe, D. D., Koonin, E. V. & Aravind, L. Evolution and classification of P-loop kinases and related proteins. J Mol Biol 333, 781-815 (2003).
3 Leipe, D. D., Wolf, Y. I., Koonin, E. V. & Aravind, L. Classification and evolution of P-loop GTPases and related ATPases. J Mol Biol 317, 41-72, doi:10.1006/jmbi.2001.5378 (2002).
4 Saraste, M., Sibbald, P. R. & Wittinghofer, A. The P-loop--a common motif in ATP- and GTP-binding proteins. Trends Biochem Sci 15, 430-434 (1990).
5 Verstraeten, N., Fauvart, M., Versees, W. & Michiels, J. The universally conserved prokaryotic GTPases. Microbiol Mol Biol Rev 75, 507-542, second and third pages of table of contents, doi:10.1128/MMBR.00009-11 (2011).
6 Walker, J. E., Saraste, M., Runswick, M. J. & Gay, N. J. Distantly related sequences in the alpha- and beta-subunits of ATP synthase, myosin, kinases and other ATP-requiring enzymes and a common nucleotide binding fold. EMBO J 1, 945-951 (1982).
7 Wittinghofer, A. GTP and ATP hydrolysis in biology. Biopolymers 105, 419-421, doi:10.1002/bip.22867 (2016).




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