Biology subjects

El Karoui, M.

Publications and source records attributed to El Karoui, M..

9 recordsLinked to original sources

bioRxiv2025

Representation learning of single-cell time-series with deep variational autoencoders

Single-cell technologies have led to many insights on the function of individual cells within populations. Time-series data, in particular, have become increasingly adopted to uncover the molecular basis of heterogeneity in processes such as gene regulation, growth adaptation, and drug resistance. Yet the analysis of single-cell trajectories often requires manual and application-dependent techniques to extract meaningful features that correlate with the biological processes of interest. Here, we employ representation learning to automatically encode time-series into a low-dimensional feature space that can be used for downstream prediction tasks. We trained deep variational autoencoders on cell length data from Escherichia coli cells growing in a "mother machine" device that allows tracking single cells over long periods. We show that the learned representations preserve the structure of the data across various growth media. Using the pretrained model in tandem with supervised learning, we encoded fresh time-series from cells exposed to single and combination antibiotics, which achieved excellent classification accuracy across drug treatments. Moreover, we demonstrate that the learned embeddings can be used to accurately classify datasets from different laboratories and growth conditions without retraining. This demonstrates that the autoencoder extracts meaningful information with promising generalization power. Our results highlight the potential of representation learning for the analysis of single-cell responses under chemical perturbations and growth conditions.

microbiology↗

bioRxiv2025

Deciphering the Replication-Division Coordination in E. coli: A Unified Mathematical framework for Systematic Model Comparison

Despite extensive research, the quantitative principles that govern the coordination between DNA replication and cell division in bacteria remain debated. Multiple theoretical models have been proposed, some postulating that a single regulatory process is sufficient to ensure replication-division coordination, while others argue that two concurrent processes are required for robust control. In this work, we develop a unifying mathematical framework within which models can be consistently formulated, qualitatively analysed and quantitatively compared. This framework also allows us to propose a new double-process model. Through theoretical analysis, we establish the necessary and sufficient conditions under which single-process models can reproduce physiological cell behaviours. Beyond the correlation-based analyses extensively used to date, we further demonstrate within a comprehensive statistical framework that double-process models more accurately recapitulate experimental data across all growth conditions. Specifically, the new model we propose robustly captures the replication-division coordination in every growth regime, thereby providing a foundation for future mechanistic studies. Author SummaryHow bacteria regulate their cell size and ensure complete chromosome replication before division remains only partly understood, posing a fundamental question. A key challenge is understanding how bacterial cells reliably distribute their genetic material to daughter cells while managing randomness in division timing, especially since DNA replication is often initiated in earlier generations. Over the past decade, several models have been developed to describe the coordination of DNA replication and cell division in Escherichia coli, combining different mechanisms and levels of complexity. These models have mainly been evaluated through correlation analysis between cell cycle parameters, such as the size at which bacteria divide or initiate DNA replication. However, such analyses depend on strong underlying assumptions that are not always met by the experimental data. Here, we present a general framework that systematically integrates multiple models, allowing both qualitative analysis and quantitative comparison without relying on correlations. Our work concludes that under all growth conditions, E. coli cells most likely divide only after meeting two combined requirements: adding a critical size since birth and a critical size since the initiation of DNA replication.

cell biology↗

bioRxiv2025

Single molecule imaging of RecB in vivo reveals dynamics of DNA Double Strand Break repair in Escherichia coli

Repairing DNA damage is of primary importance for all living organisms. DNA double-strand breaks (DSBs) are one of the most serious types of DNA damage, as they lead to loss of genetic information and death when not repaired. In E. coli, they are recognised and processed by the RecBCD complex, which initiates repair by homologous recombination. Although the repair dynamics down-stream of RecBCD has been well characterised, it is still unclear how long this complex stays attached to DNA and what triggers its dissociation in vivo. To answer these questions, we imaged RecB at the single-molecule level, and quantified its dynamic behaviour in bacterial cells exposed to ciprofloxacin, an antibiotic that induces DSBs. Our results show that RecB forms long-lived complexes with DSBs (10 seconds), and that its dissociation from DNA is an intrinsic property of the complex, that does not depend on the amount of DNA damage, nor the following steps in the repair pathway. Moreover, we show that we can use RecB binding to DSBs as a marker to estimate the rate of damage formation. This study provides a detailed quantitative insight into the interaction of RecBCD with DNA double-strand ends in E. coli in vivo, and into the bacterial response to DSBs induced by ciprofloxacin.

microbiology↗

bioRxiv2024

Suppression of bacterial cell death underlies the antagonistic interaction between ciprofloxacin and tetracycline in Escherichia coli

Antibiotic combinations are an attractive strategy to maximise the efficiency of drug treatment and minimise resistance evolution, but we still lack a full understanding of their effect on bacterial cells. The interaction between DNA-targeting antibiotics, such as ciprofloxacin, and translation inhibitors, such as tetracycline, is antagonistic, resulting in a weaker effect on bacterial growth than expected from the effect of each single drug. This antagonism has been analysed in detail at the population level, but we lack a single-cell understanding of its effect and how it depends on nutrient availability. Here, we used a microfluidic device to quantify the antagonism between ciprofloxacin and tetracycline at the single-cell level in three nutrient conditions. We showed that improved growth is due to increased survival of cells under the drug combination compared to ciprofloxacin alone. This effect is growth-dependent, with better suppression in rich nutrient conditions. Quantification of the DNA damage response (SOS response) revealed two sub-populations among the cells that die upon ciprofloxacin treatment, with some cells reaching a very high level of SOS while others had a lower level of SOS, similar to surviving cells. The low-SOS cells were more frequent in fast growth conditions and showed increased survival under the drug combination but the high-SOS cells were hardly rescued by the drug combination. This result explains the stronger antagonistic effect of tetracycline on ciprofloxacin in fast growth compared to slow growth. Our results underscore the importance of single-cell quantification in understanding the bacterial response to antibiotic combinations and devising new treatment strategies.

cell biology↗

bioRxiv2023

In vivo single-molecule imaging of RecB reveals efficient repair of DNA damage in Escherichia coli

Efficient DNA repair is crucial for maintaining genome integrity and ensuring cell survival. In Escherichia coli, RecBCD plays a crucial role in processing DNA ends following a DNA double-strand break (DSB) to initiate repair by homologous recombination. While RecBCD has been extensively studied in vitro, less is known about how it contributes to rapid and efficient repair in living bacteria. Here, we perform single-molecule microscopy to investigate DNA repair in real-time in E. coli. We quantify RecB single-molecule mobility and monitor the induction of the DNA damage response (SOS response) in individual cells. We show that RecB binding to broken DNA ends leads to efficient repair without SOS induction. In contrast, in a RecB mutant with modified activities leading to the activation of an alternative repair pathway, repair is less efficient and leads to high SOS induction. Our findings reveal how subtle alterations in RecB activity profoundly impact the efficiency of DNA repair in E. coli.

molecular biology↗

bioRxiv2023

Estimating mutation rates under heterogeneous stress responses

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that the induction of the response also reduces the division rate. Moreover, we find that in many cases, our model of heterogeneous stress responses and the standard model with mutant fitness cost reproduce fluctuation assay data equally well, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer heterogeneity in stress-induced mutation rates. Author summaryHow does environmental stress, especially from antibiotics, affect mutation rates in bacteria? This question has often been examined by estimating mutation rates using fluctuation assays, a standard experiment dating back to Luria and Delbruck in the 1940s. We address a gap in currently available estimation methods: we consider cell-to-cell variation in stress responses within bacterial populations, as revealed by recent single-cell studies. Our approach involves a population dynamic model inspired by the DNA-damage response in E. coli (SOS response). It accounts for a subpopulation with high expression of the stress response, which increases the mutation rate and decreases the division rate of a cell. Notably, we find that existing models and our heterogeneous-response model reproduce simulated fluctuation assay data equally well in certain scenarios. This emphasises the need for separate experiments to uncover the true underlying processes. Nevertheless, when stress responses are known to be heterogeneous, our study offers a novel method for accurately estimating mutation rates specifically associated with the high expression of the stress response. Uncovering the heterogeneity in stress-induced mutation rates could be important for predicting the evolution of antibiotic resistance.

evolutionary biology↗

bioRxiv2021

Fine-tuning of RecBCD expression by post-transcriptional regulation is required for optimal DNA repair in Escherichia coli

All living organisms have developed strategies to respond to chromosomal damage and preserve genome integrity. One such response is the repair of DNA double-strand breaks (DSBs), one of the most toxic forms of DNA lesions. In Escherichia coli, DSBs are repaired via RecBCD-dependent homologous recombination. RecBCD is essential for accurate chromosome maintenance, but its over-expression can lead to reduced DNA repair ability. This apparent paradox suggests that RecBCD copy numbers may need to be tightly controlled within an optimal range. Using single-molecule fluorescence microscopy, we have established that RecB is present in very low abundance at mRNA and protein levels. RecB transcription shows high fluctuations, yet cell-to-cell protein variability remains remarkably low. Here, we show that the post-transcriptional regulator Hfq binds to recB mRNA and down-regulates RecB protein translation in vivo. Furthermore, specific disruption of the Hfq-binding site leads to more efficient translation of recB mRNAs. In addition, we observe a less effective reduction of RecB protein fluctuations in the absence of Hfq. This fine-tuning Hfq-mediated mechanism might have the underlying physiological function of maintaining RecB protein levels within an optimal range.

systems biology↗

bioRxiv2021

Growth-dependent heterogeneity in the DNA damage response in Escherichia coli

In natural environments bacteria are frequently exposed to sub-lethal levels of DNA damage which leads to the induction of a stress response (the SOS response in Escherichia coli). Natural environments also vary in nutrient availability, resulting in distinct physiological changes in bacteria which may have direct implications on their capacity to repair their chromosomes. Here, we evaluated the impact of varying the nutrient availability on the expression of the SOS response induced by chronic sub-lethal DNA damage in E. coli. The expression of the SOS regulon was found to be highly heterogeneous at the single-cell level in all growth conditions. Surprisingly, we observed a larger fraction of high SOS-induced cells in slow growth as compared with fast growth, despite a higher rate of SOS induction in fast growth. This counter-intuitive result can be explained by the dynamic balance between the rate of SOS induction and the division rates of cells exposed to DNA damage. Taken together, our data illustrates how cell division and physiology come together to produce growth-dependent heterogeneity in the DNA damage response.

cell biology↗

bioRxiv2017

Quantification of very low-abundant proteins in bacteria using the HaloTag and epi-fluorescence microscopy

Cell biology is increasingly dependent on quantitative methods resulting in the need for microscopic labelling technologies that are highly sensitive and specific. Whilst the use of fluorescent proteins has led to major advances, they also suffer from their relatively low brightness and photo-stability, making the detection of very low abundance proteins using fluorescent protein-based methods challenging. Here, we characterize the use of the self-labelling protein tag called HaloTag, in conjunction with an organic fluorescent dye, to label and accurately count endogenous proteins present in very low numbers (<7) in individual Escherichia coli cells. This procedure can be used to detect single molecules in fixed cells with conventional epifluorescence illumination and a standard microscope. We show that the detection efficiency of proteins labelled with the HaloTag is [≥]80%, which is on par or better than previous techniques. Therefore, this method offers a simple and attractive alternative to current procedures to detect low abundance molecules.

systems biology↗