Pseudomonas Cold Tolerance Genomics Project

ISEF Category: Microbiology

Subcategory: Bacteriology  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

Some bacteria do not mind the fridge at all. That matters because cold storage slows many microbes, but not the ones that spoil milk and other foods. You can ask why some Pseudomonas strains keep growing while their relatives stall out. The answer may hide in their genomes.

What Is It?

This project studies psychrotrophic bacteria, which are cold-loving enough to grow in the refrigerator but usually grow best a bit warmer. Your target, Pseudomonas fluorescens, is a common food-spoilage bacterium. Think of the genome as a toolbox. Some strains carry extra tools that help them keep working in the cold, while other strains do not.

You can compare public genome sequences from cold-tolerant strains and closer relatives that prefer moderate temperatures. A pan-genome analysis groups shared genes and strain-specific genes across many genomes. That lets you ask which gene families show up more often in refrigerator-persistent strains. Then you can pair the genome data with cold-growth curves, which track how fast the bacteria grow at 4 °C versus 22 °C. That gives you both a genetic story and a real-world phenotype.

The key idea is simple. If a gene family helps cold survival, strains that grow well in the fridge should often carry it. If you see the same pattern in many genomes and in your growth data, your project becomes much stronger.

Why This Is a Good Topic

This is a strong science fair topic because you can ask a real biological question with public data and a clear phenotype. The genome side gives you a chance to do original bioinformatics, and the growth curves let you connect genes to behavior. The topic matters in food safety, since cold-tolerant bacteria can spoil milk and other refrigerated foods. You can learn comparative genomics, basic statistics, and how to link sequence data to a measurable trait.

Research Questions

• How does genome content differ between refrigerator-persistent Pseudomonas fluorescens strains and mesophilic relatives? ?
• What is the effect of cold temperature on growth rate in psychrotrophic versus mesophilic strains? ?
• Does the presence of specific gene families predict faster growth at 4 °C? ?
• To what extent do accessory genes explain variation in lag time under cold conditions? ?
• Which metabolic or membrane-related pathways are enriched in cold-tolerant strains? ?
• How does pan-genome clustering change when you include more public isolates from dairy sources? ?

Basic Materials

• A computer with enough storage for genome files and analysis outputs.
• Public genome access from NCBI Genome, Assembly, and RefSeq databases.
• Free bioinformatics software such as Roary, Prokka, and IQ-TREE or a similar phylogeny tool.
• Spreadsheet software for data tables and graphs.
• A spectrophotometer or plate reader for growth-curve measurements if your school has one.
• Sterile culture tubes, agar plates, and standard microbiology supplies from a supervised lab.
• Refrigerated incubator or cold room set near 4 °C.
• Standard incubator or shaker set near 22 °C.

Advanced Materials

• A high-performance computer or university workstation for pan-genome analysis.
• Fresh or archived BSL-1 Pseudomonas fluorescens isolates with documented source metadata.
• Selective and general-purpose microbiology media approved by the lab.
• Spectrophotometer, microplate reader, or automated growth-monitoring system.
• Refrigerated incubator and temperature-controlled shaker.
• DNA extraction kit and library prep access if you plan to resequence isolates.
• PCR setup, if you add gene confirmation or marker checks.
• Statistical software for generalized linear models or mixed-effects models.

Software & Tools

• NCBI Genome and Assembly: Finds public bacterial genomes and metadata for isolate selection.
• Prokka: Annotates bacterial genomes before pan-genome comparison.
• Roary: Builds the pan-genome and clusters shared gene families.
• IQ-TREE: Builds a phylogenetic tree from core genes so you can compare related strains.
• R: Handles growth-curve plots, statistical tests, and gene presence analysis.

Experiment Steps

1. Define your strain set and decide which public genomes count as refrigerator-persistent, dairy-linked, or mesophilic controls.
2. Standardize your annotation pipeline so every genome gets processed the same way before pan-genome comparison.
3. Build the pan-genome and choose the summary outputs that answer your gene-family question.
4. Select candidate gene families that fit a cold-survival hypothesis, such as membrane, stress-response, or metabolism genes.
5. Plan a growth comparison that measures both cold performance and a warmer reference condition with matched methods.
6. Link the genomic patterns to the phenotype with a clear statistical test and a figure that compares strain groups.

Common Pitfalls

• Mixing genomes with different assembly quality, which makes gene presence calls look biological when they are really technical.
• Treating taxonomically distant strains as direct controls, which weakens any claim about cold adaptation.
• Using growth data from different inoculum sizes or culture ages, which can fake a temperature effect.
• Calling every gene found in a cold strain a cold-adaptation gene, which ignores background lineage effects.
• Skipping metadata checks for isolate source, which can mix dairy strains with unrelated environmental isolates.

What Makes This Competitive

A strong version of this project does more than list genes. You compare many genomes, control for lineage, and test whether a gene family still predicts cold growth after the obvious confounders are removed. You also make the phenotype part strong, with repeated growth curves, clear controls, and clean statistics. If you can connect a genome pattern to a measurable cold-survival trait, your project starts to look like real research.

Project Variations

• Focus only on dairy isolates and ask which genes separate milk spoilers from other refrigerated strains.
• Replace growth curves with biofilm assays to test whether cold persistence tracks with surface attachment.
• Add transcriptomics or qPCR for a few candidate genes if your lab can measure expression at cold temperature.

Learn More

• NCBI Genome and Assembly database: Search public bacterial genomes, assemblies, and isolate metadata for strain selection.
• NCBI Pathogen Detection: Compare related bacterial isolates and explore clustering data when available.
• Roary documentation and examples: Learn how the pan-genome pipeline groups bacterial gene families.
• Pan-Genome Analysis of Bacterial Genomes in peer-reviewed journals: Search PubMed for review articles on bacterial pan-genomes and accessory genes.
• Pseudomonas review articles in PubMed: Search for reviews on cold adaptation, food spoilage, and psychrotrophic growth.
• MIT OpenCourseWare microbiology and genomics materials: Find free lecture notes and labs that explain bacterial genetics and sequence analysis.