Bacteriophages exhibit staggering genomic diversity, yet phenotypic characterization remains bottlenecked by assays that generally yield simple binary infection outcomes. Quantitative traits can be extracted from standard liquid cultures, but many phages fail to produce a measurable effect in these settings, necessitating an improved quantitative approach on semi-solid media. While end-point plaque size is commonly used for quantitative phenotyping, it only provides a static snapshot that fails to disentangle phage performance across changing bacterial growth phases. Here, we report a cost-effective, scalable method to quantify the bacterial killing rates of diverse phages by continuously tracking plaque development using a consumer-grade flatbed scanner and custom open-source computer vision software. By fitting a minimal, five-parameter phenomenological model to the diverse BASEL collection of Escherichia coli phages, we accurately captured plaque expansion dynamics across all bacterial growth phases. We discovered that plaque expansion parameters vary significantly across individual phages and taxonomic families, with the initial expansion rate demonstrating an inverse correlation with viral genome size. Notably, these plaque expansion dynamics did not correlate with bacterial collapse times in liquid culture, indicating that they represent distinct physiological and kinetic processes. Finally, we demonstrated that phage taxonomic family can be predicted with 72.1% accuracy solely from dynamic plaque parameters using a random forest classifier, whereas conventional endpoint plaque sizes held no predictive power. This time-lapse phenotyping approach yields robust kinetic data superior to end-point measurements, establishing a scalable platform to accelerate phage discovery and genotype-phenotype mapping. ### Competing Interest Statement The authors have declared no competing interest.

The authors develop SPIN-Seq, a method that directly links the sequence of individual DNA molecules to their functional behavior, revealing how DNA sequence impacts protein-DNA interactions and the ki...

Why I built a free, local, no-install tool to clean and explore multispectral 3D scanning data from the PlantEye F600, and what it actually produces.

The Robinson Lab at UCL studies childhood-onset lupus: interferon, immune phenotyping, heart and blood vessel risk, and sex differences in autoimmunity.

Artificial intelligence-enabled quantification and analyses of brown adipose tissue (BAT) activity uncover links between BAT and a healthier metabolic profile along with lower rates of psychiatric dis...

A study of 26 historic Pakistani wheat cultivars released between 1911 and 2019 combines RhizoVision digital root phenotyping with molecular screening of major breeding genes to reveal extensive

We thank Dr Lakshmanan for his thoughtful commentary regarding our recent publication1 and for highlighting important considerations in phenotyping for strabismus genetics. Although we agree with several points raised, we are concerned that a drive for phenotypic perfection could compromise scalability—and subsequent advances—in genetic research.

This retrospective case–control study followed institutional guidelines and was approved by the Institutional Review Board of Memorial Sloan Kettering Cancer Center (MSK), protocol number 17-581. The requirement for informed consent was waived because the study involved secondary analysis of previously acquired PET–CT imaging and clinical data, posed no more than minimal risk to participants and could not be conducted practically with individual informed consent. All patient data were deidentified before use. We previously established a cohort of patients with BAT by analysing 18F-FDG-PET–CT scans performed at MSK from June 2009 through March 20184. Patients who were positive for BAT in at least one scan were termed BAT+, whereas the remaining patients were grouped as BAT−. To expand this cohort, we established a new Extension BAT Cohort by following a similar strategy. We reviewed all 18F-FDG-PET–CT scans performed at MSK from patients aged 18 years and above from April 2018 through July 2024. People who were positive for BAT on at least one scan were termed BAT+, whereas the remaining patients were grouped as BAT− (Extended Data Fig. 1a and Supplementary Fig. 2). For each patient in both groups, an index scan was designated: in patients with BAT reported on at...

Abstract. Tillering affects canopy leaf area, and hence crop growth via capture of light, water and nutrients. Depending on the season, variation in tiller

Precision phenotyping combining audiometric data and genetics predicts sensorineural hearing loss far more accurately than standard billing codes.