Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Henrion, Lucas; Delvenne, Mathéo; Kakahi, Fatemeh Bajoul; Moreno-Avitia, Fabian; Delvigne, Frank

doi:10.3389/fmicb.2022.869509

Cited by 6 publications

(4 citation statements)

References 74 publications

(92 reference statements)

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“…In an attempt to reply to the first question, we previously used information theory for deriving a proxy that can be used for quantifying the degree of heterogeneity of a cell population i.e., the information entropy 33 . The computation of the entropy profile H(t) can be done based on the same binning strategy as the one developed for computing F(t) ( Supplementary note 3 ).…”

Section: Resultsmentioning

confidence: 99%

Release of extracellular DNA byPseudomonasspecies as a major determinant for biofilm switching and an early indicator for cell population control

Kang

Volke

et al. 2021

Preprint

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Microbial populations undergo phenotypic switching as a response to environmental perturbations. For instance, some bacteria switch from a planktonic lifestyle to biofilm, resulting in altered physiological properties such as increased robustness depending on the conditions. However, the precise detection of phenotypic switching events during the bacterial life cycle is still a technical challenge. Propidium iodide (PI) is one of the most frequently used fluorescence indicators for assessing cell viability based on membrane permeability, yet PI-stained cells sometimes display a red-but-not-dead phenotype. In Escherichia coli, this phenomenon is connected to modulation of porins in the outer membrane (OM) to adapt OM permeability according to nutrient availability. In this study, we explored PI staining to assess phenotypic changes in Pseudomonas sp. during biofilm development. We show that this switch is linked to excretion of extracellular DNA (eDNA), rather than modification of OM permeability. Confocal laser scanning microscopy (CLSM) enabled direct visualization of red fluorescent clusters outside intact membranes of viable cells, suggesting that PI binds eDNA. Besides, the occurrence of PI-positive sub-populations was correlated with biofilm formation in the model bacterium Pseudomonas putida KT2440. Engineered derivatives thereof with altered biofilm-forming capabilities exposed a whole continuum of phenotypic states involving planktonic cells and aggregates, and were identified according to the dynamic change of PI-positive cells with flow cytometry analysis. Our results demonstrate that PI is a fast, convenient and versatile staining for eDNA to rapidly monitor the phenotypic switching of Pseudomonas sp. during transitions in the bacterial lifestyle.

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Section: Resultsmentioning

confidence: 99%

Release of extracellular DNA byPseudomonasspecies as a major determinant for biofilm switching and an early indicator for cell population control

Kang

Volke

et al. 2021

Preprint

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“…This approach allows to maintain a cell population in a dynamic switching state during the experiment. Based on the analysis of the MI, i.e., the amount of information transferred from the extracellular conditions to the cell systems 27 , 29 , 42 , we determined that for the P araB :GFP system, the chemostat drives a similar amount of information to the Segregostat. On the other hand, we observed a drastic reduction in entropy when entraining stress-related systems, such as the P glc3 :GFP system in yeast, in Segregostat.…”

Section: Discussionmentioning

confidence: 99%

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Henrion,

Martinez,

Vandenbroucke

et al. 2023

Nat Commun

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Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.

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“…For this purpose, we derived parameters from the computation of information entropy. Information entropy is frequently used for computing the degree of phenotypic heterogeneity of mono-culture based on the spread of the phenotypes distribution 383927 . We use a similar approach for capturing the spread of one microbial species over the utilization of several MNs ( Figure 3c ).…”

Section: Resultsmentioning

confidence: 99%

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

Martinez,

Bouchat,

Gallet de Saint Aurin

et al. 2024

Preprint

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A lot of attention has been given to the understanding of microbial interactions leading to stable co-cultures, but the resulting technologies have been rarely challenged in dynamic cultivation conditions. In this work, substrate pulsing was performed to promote better control of the metabolic niches corresponding to each species, leading to the continuous co-cultivation of diverse microbial organisms. For this purpose, we used a cell-machine interface relying on automated flow cytometry, allowing to adjust the temporal profile of two metabolic niches according to a rhythm ensuring the successive growth of two species i.e., in our case a yeast and a bacterium. The resulting approach, called Automated Adjustment of Metabolic Niches (AAMN), was successfully employed for stabilizing both cooperative and competitive co-cultures. Additionally, AAMN can be considered as an enabling technology for the deployment of co-cultures in bioprocesses, demonstrated here based on the continuous bioproduction of p-coumaric acid. Taken altogether, the data accumulated suggest that AAMN could be used for a wider range of biological systems, but also to gain fundamental insights about microbial interaction mechanisms.

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Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Cited by 6 publications

References 74 publications

Release of extracellular DNA byPseudomonasspecies as a major determinant for biofilm switching and an early indicator for cell population control

Release of extracellular DNA byPseudomonasspecies as a major determinant for biofilm switching and an early indicator for cell population control

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

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