Jonathan M.
Pawl
Recent biology graduate who constructed a DNA-damage biosensor at the bench and designed AI tools that turn lab assay data into insight — working at the intersection of the bench and the algorithm.
01 — About
I'm a recent biology graduate with a builder's instinct. In the lab I engineered genetic constructs and ran assays; at the keyboard I built the software that makes data legible.
My undergraduate research focused on constructing a RAD52–GFP fusion biosensor in yeast to report on DNA-damage repair — a pathway central to BRCA-deficient cancers. Alongside the bench work, I built an AI tool that predicts whether a compound is genotoxic from its molecular structure. I was an NAIA student-athlete; disciplined, curious, and aggressive problem solver.
02 — Research Experience
Undergraduate Research
Jan – May 2026Construction & verification of a RAD52–GFP fusion — a DNA-damage biosensor engineered in S. cerevisiae to report on a repair pathway relevant to BRCA1/BRCA2-deficient cancers.
Construct a C-terminal RAD52–GFP fusion for an undergraduate genetics lab.
Develop a yeast gene-editing protocol usable in a teaching lab.
Build a eukaryotic biosensor to detect DNA-damaging agents in environmental samples.
Four fragments → one 6,847 bp construct
Six BsaI-flanked primers were designed and three gene fragments amplified by PCR (Q5 polymerase), then assembled with the backbone in a single BsaI Golden Gate reaction — 100% predicted overhang-ligation fidelity.
Amplicons total ~6,923 bp; the assembled construct is 6,847 bp because the BsaI sites and spacer bases flanking each fragment are excised during the digestion–ligation reaction. Backbone pGA-red-maxi (Addgene #196337) · donor pCEC-red (#196040) · BsaI-HFv2 · T4 ligase · NEBridge Golden Gate · native RAD52 replaced by CRISPR-Cas9.
Red/white screening recovered the recombinants
White colonies — cassette inserted, red marker lost — were the candidate correct assemblies. Several hundred were screened across replicate platings; negative controls (assembly mix alone) gave zero colonies — clean background.
Why it matters in industry. A yeast GFP DNA-damage reporter is the same assay class commercialized as the GreenScreen genotoxicity test used by pharma and chemical companies — this undergraduate project rebuilds that concept from scratch.
Primer & guide-RNA design and construct planning in Benchling and VectorBee.
Golden Gate assembly, CRISPR-Cas9 editing, plasmid cloning, bacterial transformation.
Colony screening, gel electrophoresis, plasmid prep, Sanger sequence verification.
GFP reporter readout by flow cytometry (Cytek Muse) after mutagen exposure.
03 — Projects
Two builds, one thread: making biology measurable.
AI Genotoxicity Predictor
A machine-learning companion to the wet-lab biosensor that predicts whether a chemical compound is likely to damage DNA — the same genotoxic signal the RAD52–GFP assay detects in living cells. Enter a compound name or SMILES string and it returns a probability of mutagenicity (Ames), the molecule structure, an applicability-domain check, and the model's cross-validated performance. Under the hood: RDKit ECFP4 fingerprints → a 400-tree random forest, served from a Flask dashboard.
Lab Assay Auto-Report Tool
Drop raw assay files (CSV, TSV, XLSX) into a folder and get a formatted QC report — no spreadsheet wrangling. It auto-detects the data type, from red/white recombinant colony screening to plate-reader RFU and qPCR Cq, and computes totals, per-plate %, means, hit-calls (≥3 SD) and outlier flags. Parsing, statistics and flags are deterministic code — numbers are never invented; an optional grounded Claude step writes the one-line interpretation using only the figures already computed. A watch mode regenerates reports as files land, and an "Ask your reports" box answers natural-language queries. Everything runs locally — export to HTML, CSV, JSON or PDF.
04 — Education & Honors
Ave Maria University
2022 – 2026Coursework: Genetics · Molecular Biology / Recombinant DNA · Microbiology · Cell Biology · General & Organic Chemistry · Statistics
Jonathan M. Pawl
Education
Research Experience
- Designed & constructed a RAD52–GFP fusion repair template via Golden Gate Assembly to engineer a yeast (S. cerevisiae) biosensor for DNA damage — relevant to BRCA1/BRCA2-deficient cancers.
- Designed sequence-specific primers; amplified RAD52 & GFP by PCR; verified constructs by gel electrophoresis, plasmid prep & sequence analysis (pGA-red-maxi, pCEC-red).
- Performed DNA extraction, bacterial transformation & red/white colony screening; quantified recombinant clones across replicate platings.
- Maintained sterile technique & detailed, reproducible documentation of all protocols, reagents & results.
Projects
- RAD52–GFP DNA-Damage Biosensor — engineered yeast biosensor reporting DNA-damage repair via fluorescence.
- AI Genotoxicity Predictor — ML tool that predicts whether a compound is genotoxic from its molecular structure, flagging candidates for wet-lab testing.
- Lab Assay Auto-Report Tool — local-first tool that turns raw assay files into formatted QC reports with deterministic stats and a grounded AI summary.
Technical Skills
Honors & Presentations
- St. Albert the Great Biology Research Award (2026)
- Dean's List (2022–2026); academic & athletic scholarships
- Oral Presentation, Florida Academy of Sciences Conference (2026); Poster, AMU Research Symposium (2026)
- NAIA Men's Basketball student-athlete