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🧠 Lessons from My First Research Project

What a clinical honors project taught me about real-world diagnostics

Before I started working with high-throughput genomics data and building workflows with tools like Nextflow and Python, I took my first steps into the world of molecular diagnostics through my honors project.

The study focused on the use of 16S rRNA genotyping as a diagnostic tool for infective endocarditis (IE) and blood culture-negative IE (BCNIE). A challenging condition to diagnose in clinical settings, especially in regions like South Africa where access to advanced diagnostics can vary.

Using a Sanger-based approach with universal bacterial primers, I compared molecular results to traditional culture outcomes from cardiac tissue and blood samples. It wasn’t glamorous bioinformatics — no pipelines, no metagenomics, just real-world clinical data and a lot of Excel cleaning. But it taught me:

Key Takeaways

  • Diagnostics isn’t always about shiny tech: Even a low-throughput assay like 16S rRNA sequencing can offer diagnostic value, especially for culture-negative infections.
  • Molecular results need clinical context: False positives, contaminants, or ambiguous taxonomy (e.g., Streptococcus vs. Staphylococcus) taught me that lab results mean little without patient history.
  • Sensitivity ≠ specificity: I learned to balance the excitement of detecting “something” with the caution needed in interpreting what that something really is.
  • Limitations can spark innovation: The experience made me think critically about how NGS and better bioinformatics tools (like RIPSeq or metagenomics) could improve what we were trying to do.

How It Shaped Me

This project grounded me in molecular microbiology, and helped me appreciate both the promise and pitfalls of sequencing in diagnostics. It gave me empathy for the challenges clinical labs face, and made me want to build better, more scalable bioinformatics tools. A mission I continue today through my work with microarray analysis and digital health solutions.

Conducted at PathCare Molecular Laboratory Ethical approval: CPUT/BMS-EC 2023/G4.