Technology development
Optical Pooled Screening
We first described and implemented the method that is now known as Optical Pooled Screening. Here, a pooled library of cell strains is imaged for live-cell phenotypes before they are fixed, and the individual strain’s identity is identified by in situ genotyping. The method was first described in a patent application that was made public in jan 2016 (Elf et al. 2016). Our proof-of-principle publication (Lawson et al. 2017) described live-cell single-molecule phenotyping capability in a minimal CRISPR library. Later, we published a larger CRISPRi screen for replication initiation accuracy (Camsund et al. 2020). In collaboration with the Mats Nilsson lab, we have extended the method to work with chromosomally expressed barcodes (Soares et al. 2025).
Single-molecule binding kinetics in living cells
Together with Gene-Wei Li, Johan Elf first demonstrated live-cell single-molecule tracking using stroboscopic illumination in the Xie lab (Elf et al. 2007). We also characterized the time it takes for a transcription factor to find and bind its chromosomal operator. We later used the stroboscopic method (English et al. 2011) to track freely diffusing proteins for the first time, and to introduce the concept of monitoring in vivo binding states based on diffusion constants. The paper’s results regarding RelA biology have, for good reasons, been questioned, see (Elf and Barkefors 2019). In 2013, we published tracking of individual molecules through states of binding and dissociation and to determine their binding and dissociation rates using hidden Markov model analysis (Persson et al. 2013). We have since used the single-molecule binding method to characterize intracellular search kinetics for LacI (Hammar et al. 2012, 2014), Cas9 (Jones et al. 2017), and in homologous recombination (Wiktor et al. 2021) after a double-stranded break. Together with the Hell group, we also developed Minflux (Balzarotti et al. 2017), and extended it to rapid single-molecule tracking in 3D (Amselem et al. 2023).
Rapid Antibiotic Susceptibility Testing
We have developed the fastest method to determine whether a bacterial strain is susceptible to an antibiotic by comparing the growth rate response of individual cells treated with an antibiotic to those not treated, using microfluidics and phase-contrast imaging (Baltekin et al. 2017). The method has been implemented in the PA-100 system by Sysmex-Astrego, and is used to test for antibiotic susceptibility in UTI at the point of care. The PA-100 system is on permanent display at the Science Museum in London. We have also extended the assay to include species identification after AST using FISH probing (Kandavalli et al. 2022), rapid AST for tuberculosis (Tran et al. 2025), and AST based on individual bacteria that can be obtained from a sepsis blood sample without culturing (Ahmad et al. 2025).
The next subvolume method
The next subvolume method is an algorithm for performing correct simulations of stochastic chemistry in three spatial dimensions (Elf and Ehrenberg 2004), as described by the reaction-diffusion master equation. In this algorithm, space is divided into N voxels, and the time for the next reaction in each voxel is sampled and ordered in a data structure that supports fast search. This enabled reaction-diffusion simulations that scale with log(N) rather than N in a naive Gillespie implementation. This makes it practically possible to simulate stochastic 3D systems.
In extensions, we have developed simulation software (Hattne et al. 2005), corrections to the RDME that apply when the voxel size approaches the reaction radius of the molecules (Fange et al. 2010), and tools to simulate single-molecule microscopy experiments (Lindén et al. 2016).