Biology subjects

Elf, J.

Publications and source records attributed to Elf, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Label-free identification of bacterial species using adapted vision transformers

Antibiotic resistance is an increasingly serious problem worldwide. Identifying the bacterial species can help guide antibiotic selection and improve patient outcomes. In sepsis, where every minute counts, rapid identification is particularly important, and new approaches are needed. In this study, deep learning models were trained to identify bacterial species from phase-contrast time-lapse images of cells growing in microfluidic traps, without fluorescent labels. We demonstrated this approach in two previous studies using laboratory strains. Here, the previous work is extended to clinical bacterial isolates, evaluating performance on isolates not seen during training. Furthermore, it was tested whether autofluorescence could aid species identification. Two validation sets were acquired in separate experiments from the training data, the first containing clinical-isolate traps with five species (Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae, Staphylococcus aureus and Enterobacter cloacae), imaged every two minutes, and the second containing clinical isolates of two species (E. coli and K. pneumoniae) recovered from spiked donor blood, imaged every minute. Training with the best previous CNN method achieved unsatisfactory results. Therefore, vision transformers were explored, and a self-supervised adaptation procedure was developed for pretrained DINOv3 using a frozen teacher, followed by supervised classification using time-lapse montages. Mean macro-F1 was 93.6 {+/-} 1.3% for isolates precultured in Mueller-Hinton medium using 60 frames (118 minutes) and 87.2 {+/-} 2.7% for isolates precultured in blood using 55 frames (54 minutes) (mean {+/-} sample standard deviation across training seeds). Performance was evaluated over time by increasing the number of frames available to the model during testing, and Fourier-domain filtering approximated reduced numerical aperture. The results are promising and suggest that the aperture can be decreased while retaining good results. However, further evaluation on independent isolates, experiments and patient samples is needed to establish generalization. Together with previous findings, these results bring us closer to rapid image-based diagnostics that could transform the initial treatment of acute bacterial infections by enabling better-informed antibiotic selection.

microbiology↗

bioRxiv2026

Optical pooled screening of a bacterial transposon mutagenesis library

Transposon mutagenesis is a powerful method to create deep libraries of genetically diverse cells. However, it has previously not been possible to analyze transposon libraries with respect to complex phenotypes as characterized by intracellular spatial dynamics. Here, we use optical pooled screening to characterize a transposon mutagenesis library via live cell single-particle imaging. The library is analyzed in real time, which allows us to use an optical tweezer to isolate cells with interesting phenotypes. We used the method to identify mutants with perturbations in replication initiation control in Escherichia coli, but it can in principle be used to identify genetic elements associated with any type of complex or dynamic single-cell phenotype.

microbiology↗

bioRxiv2025

The lac repressor strikes a balance between inducibility and strength of repression

Transcription factors (TFs) efficiently locate their target DNA sequences by combining three-dimensional diffusion and one-dimensional sliding on nonspecific DNA. To balance rapid sliding with strong specific binding, TFs were proposed to switch between search and recognition conformations. For E. coli lac repressor (LacI), the folding of the hinge helices has been implicated in the conformational switch. Here, we tested how mutations in the hinge region impact the search speed and binding stability. Based on molecular dynamics simulations, we selected two LacI mutants favoring either search or recognition conformation. We measured the binding kinetics of the mutants both in vitro on DNA microarrays with 2,479 different Lac operators and in vivo via single-molecule experiments. We conclude that a hinge region mutation causing less helix propensity enhances the specificity but reduces binding strength globally, while a hinge region mutation causing higher helix propensity has opposite effects. However, altered specificity impacts the search time less than expected. Instead, the major effect was impaired dissociation in response to IPTG induction for the strongly binding mutant. Together with earlier reports of affinity-inducibility trade-offs in LacI, our data support the model in which the hinge region governs a trade-off between binding stability and inducibility rather than between speed and binding stability.

molecular biology↗

bioRxiv2025

Phenotypic Antibiotic Susceptibility Testing at the limit of one bacterial cell

The blood of a patient with bacteremia contains only a few bacteria per milliliter. Recently, techniques have been developed for extracting these few bacteria from whole blood. Here, we evaluate if a phenotypic Antibiotic Susceptibility Test (AST) can be performed on a single bacterial cell by monitoring changes in its phenotypic distributions sampled over time rather than across populations, while also accounting for experimental noise and cell-to-cell variability. We use the method to estimate the time required to correctly classify single susceptible or resistant bacteria when treated with antibiotics that affect growth, cell division, or cause lysis. We find that due to heterogeneous single cell responses, it is necessary to consider all bacteria close to the susceptibility breakpoint as resistant. However, it is possible to follow up resistance calls by sequentially exposing the cell or its lineage to new antibiotics until a susceptible phenotype is detected.

microbiology↗

bioRxiv2024

A dynamic 3D polymer model of the Escherichia coli chromosome driven by data from optical pooled screening

The DNA of bacterial cells is organized in a highly dynamic chromosome structure. To guarantee its propagation, the chromosome must replicate, segregate, and accommodate other biological processes like gene expression. Therefore, to understand the causal relationship between chromosome organization and biological function, it is essential to follow chromosome dynamics. Live-cell imaging of fluorescent labels allows the tracking of specific genomic locations, but the current imaging-based approaches to study bacterial chromosome organization over the cell cycle are limited in their throughput. Even with multicolor fluorescent locus labeling, the genomic resolution is insufficient to gain insights about the whole chromosome structure from a single experiment. Although sequencing-based methods like chromosome conformation capture provide high genomic coverage, they can only be done in bulk, providing an averaged static view of the chromosome structure. In this study, we address these limitations and investigate the bacterial chromosome organization by imaging fluorescently labeled loci in a library of Escherichia coli strains, following the 3D locations of 68 different loci in live cells in a single experiment. The resulting location distributions along the cells longitudinal and radial axes are used to inform a dynamic polymer model of the chromosome over the cell cycle. We show a global reorganization of the E. coli chromosome, at both the longitudinal and radial axes. Our model reproduces the known chromosomal architecture of four macrodomains and demonstrates how these domains form dynamically over the cell cycle.

systems biology↗

bioRxiv2024

The 3D point spread function can be autoencoded in latent space

The 3D point spread function of a fluorescence emitter in a living cell is often different from that of the z-stack of bead images typically used as a reference. Here we show that the location in z of a fluorescent emitter can be directly accessed in the latent space of an autoencoder trained on the sample images without z-reference data. The corresponding decoding network represents an accurate point spread function.

biophysics↗

bioRxiv2024

Anti-correlation of LacI association and dissociation rates observed in living cells

The rate at which transcription factors (TFs) bind their cognate sites has long been assumed to be limited by diffusion, and thus independent of binding site sequence. Here, we systematically test this assumption using cell-to-cell variability in gene expression as a window into the in vivo association and dissociation kinetics of the model transcription factor LacI. Using a stochastic model of the relationship between gene expression variability and binding kinetics, we performed single-cell gene expression measurements to infer association and dissociation rates for a set of 35 different LacI binding sites. We found that both association and dissociation rates differed significantly between binding sites, and moreover observed a clear anticorrelation between these rates across varying binding site strengths. These results contradict the long-standing hypothesis that TF binding site strength is primarily dictated by the dissociation rate, but may confer the evolutionary advantage that TFs do not get stuck in near-operator sequences while searching.

biophysics↗

bioRxiv2024

Culture-free Rapid Isolation and Detection of Bacteria from Whole Blood at Clinically Relevant Concentrations

Approximately 50 million people suffer from sepsis yearly, and 13 million die from it. For every hour a patient with septic shock is untreated, their survival rate decreases by 8%. Therefore, rapid detection and antibiotic susceptibility profiling of bacterial agents in the blood of sepsis patients are crucial for determining appropriate treatment. The low bacteria concentrations and high abundance of blood cells currently necessitate culture-based diagnostic methods, which can take several days. Here, we introduce a method to isolate bacteria from whole blood with high separation efficiency through smart centrifugation, followed by microfluidic trapping and subsequent detection using deep learning applied to microscopy images.

bioengineering↗

bioRxiv2024

One-day phenotypic drug susceptibility testing for Mycobacterium tuberculosis variant bovis BCG using single-cell imaging and a deep neural network

Drug-resistant tuberculosis (TB) kills approximately 200,000 people every year. A contributing factor is the slow turnaround time associated with anti-tuberculosis drug susceptibility diagnostics. The prevailing gold standard for phenotypic drug susceptibility testing (pDST) takes at least two weeks. In this study, we used Mycobacterium tuberculosis variant bovis BCG (M. bovis BCG) and Mycobacterium smegmatis as models for tuberculous and nontuberculous pathogens. The bacteria were loaded into a microfluidic chip, trapping them in microchambers, and allowing simultaneous tracking of single-cell growth with and without antibiotic exposure. A deep neural network image-segmentation algorithm was employed to quantify the growth rate over time and determine how the strains responded to the drugs compared to the untreated reference. We determined that the response time of the susceptible strains to isoniazid (INH), ethambutol (EMB), and linezolid (LZD) at MIC was within 3 hours and 1.5 hours for M. bovis BCG and M. smegmatis, respectively. Resistant strains of M. smegmatis were identifiable within 3 hours, suggesting that growth-based pDST can be conducted in less than 12 hours for slow-growing M. bovis BCG. The results obtained for M. bovis BCG are most likely comparable to what we expect for M. tuberculosis as these strains share 99.96% genetic identity.

microbiology↗

bioRxiv2023

Pooled optical screening in bacteria using chromosomally expressed barcodes

Optical pooled screening is an important tool to study dynamic phenotypes for libraries of genetically engineered cells. However, the desired engineering often requires that the barcodes used for in situ genotyping are expressed from the chromosome. This has not been possible in bacteria. Here we describe a method for in situ genotyping of libraries with genomic barcodes in Escherichia. coli. The method is applied to measure the intracellular maturation time of 81 red fluorescent proteins.

biophysics↗

bioRxiv2023

Three-dimensional localization of fluorescent proteins in living Escherichia coli

3D localization of fluorescent proteins (FPs) in living bacteria has been challenging due to the low signal-to-background ratio of the FPs and the relatively uncertain positioning of the cells in the optical reference system. Using mother-machine microfluidic devices together with deep learning, we present an approach that enables accurate 3D localization of FPs in Escherichia coli over long periods. We describe a method to simulate ground truth training data for the deep learning network based on background models generated from experimental data. We test the method by studying how chromosomal loci are relocated in 3D over the E. coli cell cycle. Since the cells are radially symmetric, we expect the same width and height distribution of fluorophores if the 3D positions are correctly determined. We observe this pattern experimentally for all the labelled loci on the chromosome. Interestingly, some loci are located exclusively in the periphery of the nucleoid, while others are more confined to the core of the nucleoid. This method enables studying any chromosomal loci inside living E. coli cells in high-throughput.

biophysics↗

bioRxiv2023

Real-time pooled optical screening with single-cell isolation capability.

In a pooled optical screen, a genetically diverse library of living cells is imaged and characterised for phenotypic variations without knowing the genotype of the cells. The genotypes are identified in situ after the cells have been fixed or by physical extraction of interesting phenotypes followed by sequencing. Mother-machine microfluidics devices are efficient tools in pooled optical screens since many strains can be imaged in the same field of view, but the throughput is often limited. In this work, we show a method to extract single bacterial cells from a compact 100,000-trap mother-machine-based fluidic device using an optical tweezer. Unlike previous devices, the fluids in our design are routed in 3D to enable fast loading of cells, increased trap density, and faster imaging. We have also developed software that allows real-time analysis of the phenotyping data.

biophysics↗

bioRxiv2023

The Escherichia coli chromosome moves to the replisome

The replisome, a large multi-subunit assembly, carries out the process of chromosome replication, connecting the unwrapping of the parental DNA with the creation of new daughter strands. In Escherichia coli, it is debated whether the two replisomes move independently along the two chromosome arms during replication or if they remain in close proximity, with the DNA being pulled toward the replisomes as replication progresses. Here, we use fluorescence microscopy to determine the location and diffusivity of the replisome and various chromosomal loci throughout the cell cycle of the model organism E. coli. We find that (i) the two replisomes are confined to a region of 250 nm and 120 nm along the cell long and short axis respectively, and the chromosomal loci move through this region sequentially based on distance from the origin of replication. (ii) When a locus is being replicated, its diffusivity slows down. (iii) There is no indication that replication initiation occurs close to the cell membrane as has been proposed in a few previous studies. In conclusion, our data supports a model with DNA moving towards stationary replisomes at replication.

microbiology↗

bioRxiv2023

Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy

Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safeguarding public health. For instance, identifying the species and its antibiotic susceptibility is vital for effective bacterial infection treatment. Here we show that phase contrast time-lapse microscopy combined with deep learning is sufficient to discriminate four species of bacteria relevant to human health. The classification is performed on living bacteria and does not require fixation or staining, meaning that the bacterial species can be determined as the bacteria reproduce in a microfluidic device, enabling parallel determination of susceptibility to antibiotics. We assess the performance of convolutional neural networks and vision transformers, where the best model attained a class-average accuracy exceeding 98%. Our successful proof-of-principle results suggest that the methods should be challenged with data covering more species and clinically relevant isolates for future clinical use. Author SummaryBacterial infections are a leading cause of premature death worldwide, and growing antibiotic resistance is making treatment increasingly challenging. To effectively treat a patient with a bacterial infection, it is essential to quickly detect and identify the bacterial species and determine its susceptibility to different antibiotics. Prompt and effective treatment is crucial for the patients survival. A microfluidic device functions as a miniature "lab-on-chip" for manipulating and analyzing tiny amounts of fluids, such as blood or urine samples from patients. Microfluidic chips with chambers and channels have been designed for quickly testing bacterial susceptibility to different antibiotics by analyzing bacterial growth. Identifying bacterial species has previously relied on killing the bacteria and applying species-specific fluorescent probes. We introduce deep learning models as a fast and cost-effective method for identifying bacteria species directly from phase-contrast microscopy images of living bacteria simultaneously as growth is analyzed. We envision this method being employed concurrently with antibiotic susceptibility tests in future applications, significantly enhancing bacterial infection treatments.

bioinformatics↗

bioRxiv2022

Antibiotic perseverance increases the risk of resistance development

The rise of antibiotic-resistant bacterial infections poses a global threat. Antibiotic resistance development is generally studied in batch cultures which conceals the heterogeneity in cellular responses. Using single-cell imaging, we studied the growth response of Escherichia coli to sub-inhibitory and inhibitory concentrations of nine antibiotics. We found that the heterogeneity in growth increases more than what is expected from growth rate reduction for five out of the nine antibiotics tested. For two antibiotics (rifampicin and nitrofurantoin), we found that sub-populations were able to maintain growth at lethal antibiotic concentrations for up to 10 generations. This perseverance of growth increased the effective population size and led to an up to 40-fold increase in antibiotic resistance development in Gram-negative and Gram-positive species. We conclude that antibiotic perseverance is a common phenomenon across the bacterial kingdom that has the potential to impact antibiotic resistance development.

microbiology↗

bioRxiv2022

Real-time single-molecule 3D tracking in E. coli based on cross-entropy minimization

Sub-ms 3D tracking of individual molecules in living cells is an important goal for microscopy since it will enable measurements at the scale of diffusion limited macromolecular interactions. Here, we present a 3D tracking principle based on the true excitation point spread function and cross-entropy minimization for position localization of moving fluorescent reporters that approaches the relevant regime. When tested on beads moved on a stage, we reached 67nm lateral and 109nm axial precision with a time resolution of 0.84 ms at a photon count rate of 60kHz, coming close to the theoretical and simulated predictions. A critical step in the implementation was a new method for microsecond 3D PSF positioning that combines 3D holographic beam shaping and electro-optical deflection. For the analysis of tracking data, a new point estimator for diffusion was derived and evaluated by a detailed simulation of the 3D tracking principle applied to a fictive reaction-diffusion process in an E. coli-like geometry. Finally, we successfully applied these methods to track the Trigger Factor protein in living bacterial cells. Overall our results show that it is possible to reach sub-millisecond live-cell single-molecule tracking, but that it is still hard to resolve state transitions based on diffusivity at this time scale.

biophysics↗

bioRxiv2021

Rapid antibiotic susceptibility testing and species identification for mixed infections

Antimicrobial resistance is an increasing problem globally. Rapid antibiotic susceptibility testing (AST) is urgently needed in the clinic to enable personalized prescription in high-resistance environments and limit the use of broad-spectrum drugs. Previously we have described a 30 min AST method based on imaging of individual bacterial cells. However, current phenotypic AST methods do not include species identification (ID), leaving time-consuming plating or culturing as the only available option when ID is needed to make the sensitivity call. Here we describe a method to perform phenotypic AST at the single-cell level in a microfluidic chip that allows subsequent genotyping by in situ FISH. By stratifying the phenotypic AST response on the species of individual cells, it is possible to determine the susceptibility profile for each species in a mixed infection sample in 1.5 h. In this proof-of-principle study, we demonstrate the operation with four antibiotics and a mixed sample with four species.

microbiology↗

bioRxiv2021

The spatial organization of replication is determined by cell size independently of chromosome copy number

Escherichia coli coordinates replication and division cycles by initiating replication at approximately the same size per chromosome at all growth rates. By tracking replisomes in individual cells through thousands of division cycles, we have dissected the mechanism behind this precise process. We have characterized wild-type cells grown under different conditions and also many mutants related to the expression and binding states of the initiator protein DnaA. This rich data set allowed us to compare the relative importance of all previously described control systems. We found that the replication initiation size regulation is not strongly dependent on the absolute concentration of DnaA, nor does it depend on active dnaA expression. Replication initiation is also not consistently triggered by cell division or replication termination. In contrast, some of the factors that convert DnaA between its ATP- and ADP-bound states have a strong effect on initiation size. We suggest a plausible model for DnaA-ATP mediated triggering of initiation at fast growth, where regulatory inactivation of DnaA (RIDA) is the main system for monitoring the number of chromosomes during active replication.

microbiology↗