Biology subjects

Hollo, G.

Publications and source records attributed to Hollo, G..

6 recordsLinked to original sources

bioRxiv2026

Harnessing Escherichia coli motility to engineer bacterial Voronoi patterns

Cell motility drives spatial pattern formation across diverse biological systems. Here, we engineer Escherichia coli motility in semi-solid agar to control Voronoi patterns in two and three dimensions, partitioning space into regions closest to their respective inoculation seeds. Consistent with our reaction-diffusion model, we observed that collisions between expansion fronts generate either biomass depletion (''gaps'') or accumulation (''anti-gaps''), governed by the relative diffusion rates of bacteria and nutrients. By engineering strains with distinct expansion rates and tuneable motility, and by integrating these experimental data into a dynamic Voronoi model, we achieved precise control over pattern geometry. This enabled the generation of gaps with varying widths, curved boundaries, asymmetric structures, seedless regions, and complex composite patterns. Together, these findings establish bacterial Voronoi patterns as a programmable platform for engineering multicellular spatial organization, with potential applications in synthetic biology and materials science.

synthetic biology↗

bioRxiv2025

An engineered multi-step differentiation program in Escherichia coli for self-organized spatial patterning

In nature, complex multicellular structures originate from individual cells containing all essential information for differentiation, patterning and morphogenesis. Synthetic biology enables a bottom-up approach to study these processes by engineering and combining individual modules to progressively increase the systems complexity. Here, we engineered a multi-step program mimicking cell differentiation in the model prokaryote Escherichia coli. Starting from genetically identical cells and without providing any external positional information, we generated autonomous spatial patterns of colonies on a solid surface. We first employed a toggle switch to break population homogeneity (symmetry breaking), stochastically differentiating cells into two subpopulations: senders and receivers. Next, we activated expression of a third reporter in receiver colonies located in close proximity to sender colonies via quorum-sensing based communication (paracrine signaling). Finally, we mimic maturation of the newly emerged population by expressing a fourth reporter via an orthogonal, self-activating, quorum sensing signal (autocrine signaling). The diversity of spatial patterns generated by this multi-step program was accurately captured by simulations of a corresponding mathematical model. Together, these results demonstrate that multi-step differentiation programs can be engineered in unicellular bacteria to drive fully self-organized spatial pattern formation.

synthetic biology↗

bioRxiv2025

Intracellularly Coupled Oscillators for Synthetic Biology

Synthetic biology aims to engineer or re-engineer living systems. To achieve increasingly complex functionalities, it is beneficial to use higher-level building blocks. In this study, we focus on oscillators as such building blocks, propose novel oscillator-based circuit designs and model the interactions of intracellularly coupled oscillators. We classify these oscillators on the basis of coupling strength: independent, weakly or strongly, and deeply coupled. We predict a range of fascinating dynamic behaviours to arise in these systems, such as the beat phenomenon, amplitude and frequency modulation, period doubling, higher-period oscillations, chaos, resonance, and synchronization, with the aim of guiding future experimental work in bacterial synthetic biology. Finally, we outline potential applications, including oscillator-based computing that integrates processing and memory functions, offering multistate and nonlinear processing capabilities.

synthetic biology↗

bioRxiv2024

GRN modeler: An Intuitive Tool for Constructing and Evaluating Gene Regulatory Networks and its Applications to Oscillators and a Light Biosensor

Modeling and simulating gene regulatory networks (GRNs) is crucial for understanding biological processes, predicting system behavior, guiding the design of synthetic biological systems, and interpreting experimental data. In synthetic biology, GRNs play a pivotal role in enabling the design and control of complex systems for a wide range of applications. However, GRN simulations can be time-consuming and often require specialized expertise. To make this process more accessible, we developed a user-friendly application with a graphical user interface (GUI), allowing users to create simple phenomenological models without requiring prior programming experience. We demonstrate the versatility of our tool through several examples, including the design of novel oscillator families capable of robust oscillation with an even number of nodes. These complement the well-known repressilator family, which only oscillates with odd-numbered nodes. Furthermore, we showcase how GRN modeler allowed us to develop a light-detecting biosensor in Escherichia coli that can track light intensity over several days, leaving a record in the form of ring patterns in bacterial colonies. In summary, our work empowers biologists to model their systems of interest even without programming expertise.

synthetic biology↗

bioRxiv2024

Engineering microbial consortia: uptake and leakage ratedifferentially shape community arrangement and composition

Bacteria often grow as communities in intricate spatial arrangements on surfaces and interact with each other through the local exchange of diffusible molecules. Yet, our understanding of how these interactions shape the properties of the communities remains limited. Here, we study synthetic communities of Escherichia coli amino acid auxotrophs interacting through the obligate exchange of amino acids. We genetically engineer these strains to alter their amino acid leakage and uptake abilities. We then characterise the spatial arrangement and composition of the communities when grown on a surface. By integrating experimental data with mathematical modeling, we demonstrate that amino acid uptake and leakage rates are crucial determinants of community structure. Our results show that while the spatial arrangement of the community is primarily governed by uptake rates, the community composition is predominantly influenced by leakage rates. These findings enhance our understanding of microbial community dynamics and provide a framework for predicting and engineering microbial consortia.

microbiology↗

bioRxiv2024

From resonance to chaos: modulating spatiotemporal patterns through a synthetic optogenetic oscillator

Oscillations are a recurrent phenomenon in biological systems across scales, including circadian clocks, metabolic oscillations and embryonic genetic oscillators. Despite their fundamental significance in biology, deciphering core principles of biological oscillators is very challenging due to the multiscale complexity of genetic networks and the difficulty in perturbing organisms in vivo. In this study, we tackle this challenge by re-designing the well-characterised synthetic oscillator, known as "repressilator", in Escherichia coli and controlling it using optogenetics, thus introducing the "optoscillator". When we apply periodic light pulses, the optoscillator behaves as a forced oscillator. Bacterial colonies harboring synthetic oscillators manifest oscillations as spatial ring patterns. Leveraging this feature, we systematically investigate the number, intensity and sharpness of the rings under different regimes of light exposure. By integrating experimental approaches with mathematical modeling, we show that this simple oscillatory circuit can generate complex dynamics that, depending on the external periodic forcing, are transformed into distinct spatial patterns. We report the observation of synchronisation, resonance, undertone and period doubling. Furthermore, we present evidence supporting the existence of a chaotic regime. This work highlights the intricate spatiotemporal patterns accessible by synthetic oscillators and underscores the potential of our approach in understanding the underlying principles governing biological oscillations.

synthetic biology↗