About
I’m a microbial evolution researcher finishing my PhD in the Behringer Lab at Vanderbilt University. My dissertation work sits at the intersection of bacterial epigenetics, experimental evolution, and statistical genomics.
Research
Bacterial DNA methylation. I produced the most detailed per-site characterization of the E. coli Dam methylome to date. Despite near-saturating bulk methylation (~96.6% at GATC sites), 177 double-stranded sites are reproducibly hypomethylated — and these cluster specifically at regulatory DNA-protein interaction sites: −35 promoter elements, CRP/Fis/Fnr binding motifs, prophage regions, and insertion sequences. I also characterized how methylation patterns diverge in the absence of methyl-directed mismatch repair, finding broader, more variable, and non-deterministic methylation loss at sites already predisposed to lower methylation. Published in mBio (2023).
Bayesian fitness genomics. I developed a Bayesian hierarchical model (Stan/brms) for longitudinal RB-TnSeq — a genome-scale fitness assay — that resolves time-dependent selection rates across the full E. coli growth curve, from exponential through long-term stationary phase. Using this framework, I constructed an empirical one-dimensional fitness seascape: a latent phenotypic axis organizing ~3,000 transposon mutant genotypes, with axis position predicting evolutionary arrival time in an independent long-term evolution experiment. In review at Molecular Biology and Evolution (bioRxiv).
Software. I developed commaKit, an R package for differential bacterial DNA methylation analysis. It was built alongside the mBio paper because no adequate tool existed; it has since been substantially rewritten with full tests and documentation and is pending Bioconductor submission. Full documentation at carl-stone.github.io/comma.
Background
Before Vanderbilt, I was a research assistant in the Brinsmade Lab at Georgetown University (2018–2020), studying nutritional regulation of virulence in Staphylococcus aureus. Before that, I completed an undergraduate honors thesis at the University of Minnesota benchmarking microbial community ecology tools (mothur, QIIME, DADA2).
What I’m Looking For
I’m graduating in May 2026 and seeking postdoc or scientist positions in computational microbiology. I work at the intersection of Bayesian statistical modeling, omics data analysis, and experimental microbiology — and I’m particularly interested in roles that add microscopy-based phenotypic analysis or mouse models to my toolkit. Geographically, I’m targeting the Chicago metro area.
If you’re interested in talking science or discussing a potential position, reach out at carl.j.stone@vanderbilt.edu.