ReviewNature protocols2026
Simple large-scale quantitative phenotyping and antimicrobial susceptibility testing with Q-PHAST.
Review in Nature protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Uncovering actionable trade-offs of antifungal resistance in a yeast pathogen.Molecular systems biology · 2026Article
- Antifungal and anti-virulence activities of cinnamon, thyme, and clove essential oils againstFrontiers in pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The characterization of antimicrobial susceptibility and other relevant phenotypes in large collections of microbial isolates is a common need across research and clinical microbiology laboratories. Robotization provides unprecedented throughput but involves costs that are prohibitive for the average laboratory. Here, using affordable materials and open-source software, we developed Q-PHAST (Quantitative PHenotyping and Antimicrobial Susceptibility Testing), a unique solution for cost-effective, large-scale phenotyping in a standard microbiology laboratory. Single colonies are grown in a deep 96-well master plate, from which diluted aliquots are used to generate 96 spots on different experimental plates containing solid medium with the substance and concentration of interest. These plates are incubated on inexpensive flatbed scanners that monitor the growth of each spot by obtaining images every 15 min. A simple, python-based software, which can be used via a graphical interface on various operating systems ( https://github.com/Gabaldonlab/Q-PHAST ), analyzes the images to infer growth, fitness (e.g., doubling rate) and susceptibility (e.g., minimum inhibitory concentration) measures. With <120 min of hands-on time per day for three consecutive days, ready-to-use results are obtained and presented in tables or graphs. This solution enables non-experts with limited resources to perform accurate quantitative phenotyping on hundreds of strains in parallel.
Indexed as
Identifiers
40355749What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.