bioRxivSynthetic BiologyPreprint
Exact-match search with functional variant prediction enables automated DNA screening
Dana GrettoniD, Brian WangiD, Rey EdisoniD, Leonard Newton FoneriD, Jens BerlipsiD, Theia VogeliD, Martin Kysel, W Q Chen, Francesca Sage-LingiD, Lynn Van Hauwe, Stephen Wooster, Helena CozzariniiD, Ben Weinstein-RauniD, Erika Alden DeBenedictisiD, Andrew Bo LiuiD, Emma J. ChoryiD, Hongrui CuiiD, Xiang LiiD, Jiangbin Dong, Andrés FábregaiD, Christianne Dennison, Otilia Don, Cassandra Tong YeiD, Kaveri I. UberoyiD, Ronald L. RivestiD, , Kevin M. EsveltiD
Abstract
Custom DNA synthesis underpins modern biology, but controlled genes in the wrong hands could threaten many lives and public trust in science. In .1992, a virology-trained mass murderer tried and failed to obtain physical samples of Ebola; today, viruses can be assembled from synthetic DNA fragments. Screening orders for controlled sequences is unreliable and expensive because current similarity search algorithms yield false alarms requiring expert human review. Exact-match search can achieve perfect specificity among short known sequences by detecting subsequences unique to controlled genes, but can be trivially evaded by incorporating mutations. Here we rescue exact-match search by additionally screening for predicted functional variants of pseudo-randomly chosen subsequences that arent found in known unregulated genes. To experimentally assess robustness, we protected nine windows from the M13 bacteriophage virus, then invited a "red team" to launch up to 21,000 attacks at each window and measure the fitness of their designed mutants. We identified defensible windows from regulated pathogens, built a test database that our experiments indicate will block 99.999% of functional attacks, and verified its sensitivity against redesigned enzymes. Exact-match search with functional variant prediction offers a promising way to safeguard biotechnology by automating DNA synthesis screening. SummarySearching for exact matches to pre-computed functional variants unique to controlled genes enables sensitive, secure, and automated DNA synthesis screening.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 4
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- DNAS-Bench: Deterministic Nucleic Acid Screener Benchmarking
Henry C. Wong, Tadayoshi Kohno, Jeff Nivala·IEEE Security and Privacy Workshops (SPW)Peer-reviewed·May 21, 2026
- Defending Synthetic DNA Orders Against Splitting-Based Obfuscation
Shaked Tayouri, Vladislav Kogan, … Rami Puzis·bioRxiv·Mar 12, 2025
- Bypassing Current Biosecurity Screens with AI Designed Proteins and Closing the Gap with Edge-AI Functional Screening
Mackenzie Noon, Grace Oualline·bioRxiv·Oct 20, 2026
- Toward AI-Resilient Screening of Nucleic Acid Synthesis Orders: Process, Results, and Recommendations
Bruce J. Wittmann, Tessa Alexanian, … Eric Horvitz·bioRxiv·Dec 2, 2024
- Inter-tool analysis of a NIST dataset for assessing baseline nucleic acid sequence screening
Tyler S. Laird, Kevin Flyangolts, … Samuel P. Forry·Applied BiosafetyPeer-reviewed·Dec 26, 2025
- Developing a Standard Definition for Sequences of Concern
Tessa Alexanian, Jacob Beal, … Nicole E. Wheeler·Frontiers in Bioengineering and BiotechnologyPeer-reviewed·Jun 4, 2026