Sarshad Koderivalappil

Postdoctoral fellow at Lawrence Berkeley National Laboratory, building tools to watch phages and bacteria evolve against each other in real time.

Hand-drawn animated line: a phage bounds up to a bacterium, lands on it and bursts it into new phages; a survivor with a different surface shrugs the next phage off, which reels away dizzy; then a phage whose fibres grip the new surface arrives. — A phage finds a host, bursts it, meets a survivor it can’t grip — and adapts. Repeat, forever.

About

I’m fascinated by how small genetic shifts, like a single mutation in a viral protein or in a host receptor, can tip the balance of an entire ecosystem. That curiosity has pulled me from clinical phage isolates in Hungary to a technology bench at Berkeley, and it’s the through-line in everything below.

Most of my current work is a bet that the coevolutionary arms race has some rules we can learn well enough to design against. So I build methods that let us watch evolution in real-time at the lineage level, rather than reconstructing it afterward. This includes dual-barcoded tracking of bacteria and their parasite phages together, enabling us to visualize both sides of the evolutionary race simultaneously.

I’m in the Environmental Genomics and Systems Biology Division at Lawrence Berkeley National Laboratory. Before that, a PhD at the University of Szeged on phage–antibiotic interplay in multidrug-resistant Pseudomonas.

Research

High-resolution lineage tracking of host–parasite evolution Dual-barcode technology that follows host and phage lineages simultaneously, turning a coevolution experiment into something you can read as it unfolds. Berkeley Lab, 2023–present.
Training phages onto receptors their ancestors could not use Deep experimental evolution of “prime” phages, asking how far host range can be pushed and which mutations get you there. University of Szeged.
Phage resistance and the cost of surviving it Coevolution that leaves multidrug-resistant Pseudomonas aeruginosa phage-resistant but antibiotic-sensitive again — the trade-off that makes phage therapy interesting.
Editing phage genomes without counterselection Targeted DNA nicking for efficient, single-step edits.

Recent publications

Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa. bioRxiv, 2026.
Targeted DNA nicking enables efficient, single-step and counterselection-free editing of bacteriophage. bioRxiv, 2026.
Scaling phage–bacteria interaction contexts: from pairwise mechanisms to community dynamics. Annual Review of Virology, vol. 13, 2026. In press.
Gradient metapopulation microfluidic ecologies shape genetic and biofilm drivers of T4r phage resistance in E. coli. npj Biofilms and Microbiomes, 2026.

All publications →

Excited about

Watching an arms race one lineage at a time

September 2026

My own, and the one I’m most impatient about: barcode the host and the phage separately, and a coevolution experiment stops being a summary statistic.

All notes →

Education