Intercellular adhesion promotes clonal mixing in growing bacterial populations

WebCM: A Web-Based Platform for Multiuser Individual-Based Modeling of Multicellular Microbial Populations and Communities

WebCM is a web platform that enables users to create, edit, run, and view individual-based simulations of multicellular microbial populations and communities on a remote compute server. WebCM builds upon the simulation software CellModeller in the back end and provides users with a web-browser-based modeling interface including model editing, execution, and playback. Multiple users can run and manage multiple simulations simultaneously, sharing the host hardware. Since it is based on CellModeller, it can utilize both GPU and CPU parallelization. The user interface provides real-time interactive 3D graphical representations for inspection of simulations at all time points, and the results can be downloaded for detailed offline analysis. It can be run on cloud computing services or on a local server, allowing collaboration within and between laboratories.

Genetic mixing and demixing on expanding spherical frontiers

Genetic fluctuation during range expansion is a key process driving evolution. When a bacterial population is expanding on a 2D surface, random fluctuations in the growth of the pioneers at the front line cause a strong demixing of genotypes. Even when there is no selective advantage, sectors of low genetic diversity are formed. Experimental studies of range expansions in surface-attached colonies of fluorescently labelled micro-organisms have contributed significantly to our understanding of fundamental evolutionary dynamics. However, experimental studies on genetic fluctuations in 3D range expansions have been sparse, despite their importance for tumour or biofilm development. We encapsulated populations of two fluorescent Escherichia coli strains in inoculation droplets (volumes [Formula: see text] nl). The confined ensemble of cells grew when embedded in a hydrogel-with nutrients-and developed 3D colonies with well-defined, sector-like regions. Using confocal laser scanning microscopy, we imaged the development of 3D colonies and the emergence of sectors. We characterized how cell concentration in the inoculation droplet controls sectors, growth rate, and the transition from branched colonies to quasi-spherical colonies. We further analysed how sectors on the surface change over time. We complement these experimental results with a modified 3D Eden growth model. The model in 3D spherical growth predicts a phase, where sectors are merging, followed by a steady increase (constant rate), and the experimentally analysed sectors were consistent with this prediction. Therefore, our results demonstrate qualitative differences between radial (2D) and spherical (3D) range expansions and their importance in gene fixation processes.

Collective protection against the type VI secretion system in bacteria

Bacteria commonly face attacks from other strains using the type VI secretion system (T6SS), which acts like a molecular speargun to stab and intoxicate competitors. Here we show how bacteria can work together to collectively defend themselves against these attacks. This project began with an outreach activity: while developing an online computer game of bacterial warfare, we noticed that one strategist ("Slimy") that made extracellular polymeric substances (EPS) was able to resist attacks from another strategist that employed the T6SS ("Stabby"). This observation motivated us to model this scenario more formally, using dedicated agent-based simulations. The model predicts that EPS production can serve as a collective defence mechanism, which protects both producing cells and neighbouring cells that do not make EPS. We then tested our model with a synthetic community that contains a T6SS-wielding attacker (Acinetobacter baylyi), and two T6SS-sensitive target strains (Escherichia coli) that either secrete EPS, or not. As predicted by our modelling, we find that the production of EPS leads to collective protection against T6SS attacks, where EPS producers protect each other and nearby non-producers. We identify two processes that explain this protection: EPS sharing between cells and a second general mechanism whereby groups of resistant cells shield susceptible cells, which we call "flank protection". Our work shows how EPS-producing bacteria can work together to defend themselves from the type VI secretion system.

Big data and machine learning driven bioprocessing - Recent trends and critical analysis

Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) was employed to explore the direction of the research domain. All the papers from 2013 to 2022 with specific keywords of bioprocessing using AI were extracted from Scopus and grouped into two five-year periods of 2013-to-2017 and 2018-to-2022, where the past and recent research directions were compared. Based on this procedure, selected sample papers from recent five years were subjected to further review and analysis. The result shows that 50% of the publications in the past five-year focused on topics related to hybrid models, ANN, biopharmaceutical manufacturing, and biorefinery. The summarization and analysis of the outcome indicated that implementing AI could improve the design and process engineering strategies in bioprocessing fields.

Spatial self-organization of metabolism in microbial systems: A matter of enzymes and chemicals

Most bacteria live in dense, spatially structured communities such as biofilms. The high density allows cells to alter the local microenvironment, whereas the limited mobility can cause species to become spatially organized. Together, these factors can spatially organize metabolic processes within microbial communities so that cells in different locations perform different metabolic reactions. The overall metabolic activity of a community depends both on how metabolic reactions are arranged in space and on how they are coupled, i.e., how cells in different regions exchange metabolites. Here, we review mechanisms that lead to the spatial organization of metabolic processes in microbial systems. We discuss factors that determine the length scales over which metabolic activities are arranged in space and highlight how the spatial organization of metabolic processes affects the ecology and evolution of microbial communities. Finally, we define key open questions that we believe should be the main focus of future research.

Calibrating spatiotemporal models of microbial communities to microscopy data: A review

Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.

4-bit adhesion logic enables universal multicellular interface patterning

Multicellular systems, from bacterial biofilms to human organs, form interfaces (or boundaries) between different cell collectives to spatially organize versatile functions^1,2. The evolution of sufficiently descriptive genetic toolkits probably triggered the explosion of complex multicellular life and patterning^3,4. Synthetic biology aims to engineer multicellular systems for practical applications and to serve as a build-to-understand methodology for natural systems^5–8. However, our ability to engineer multicellular interface patterns^2,9 is still very limited, as synthetic cell–cell adhesion toolkits and suitable patterning algorithms are underdeveloped^5,7,10–13. Here we introduce a synthetic cell–cell adhesin logic with swarming bacteria and establish the precise engineering, predictive modelling and algorithmic programming of multicellular interface patterns. We demonstrate interface generation through a swarming adhesion mechanism, quantitative control over interface geometry and adhesion-mediated analogues of developmental organizers and morphogen fields. Using tiling and four-colour-mapping concepts, we identify algorithms for creating universal target patterns. This synthetic 4-bit adhesion logic advances practical applications such as human-readable molecular diagnostics, spatial fluid control on biological surfaces and programmable self-growing materials^5–8,14. Notably, a minimal set of just four adhesins represents 4 bits of information that suffice to program universal tessellation patterns, implying a low critical threshold for the evolution and engineering of complex multicellular systems^3,5.

A synthetic cell-cell adhesion logic using swarming E. coli with 4 bits of information is introduced, enabling the programming of interfaces that combine to form universal tessellation patterns over a large scale.

High rates of plasmid cotransformation in E. coli overturn the clonality myth and reveal colony development

The concept of DNA transfer between bacteria was put forth by Griffith in 1928. During the dawn of molecular cloning of DNA in the 1980s, Hanahan described how the transformation of DNA plasmids into bacteria would allow for cloning of DNA fragments. Through this foundational work, it is widely taught that a typical transformation produces clonal bacterial colonies. Using low concentrations of several plasmids that encode different fluorescent proteins, under the same selective antibiotic, we show that E. coli bacteria readily accept multiple plasmids, resulting in widespread aclonality and reveal a complex pattern of colony development. Cotransformation of plasmids occurs by either CaCl2 or by electroporation methods. A bacterium rod transformed with three plasmids-each expressing a high level of a unique fluorescent protein-and replated on agar, appears to reassign a random number of the three fluorescent plasmids to its daughter cell during cell division. The potential to simultaneously follow multiple lineages of clonally related bacteria in a bacteria colony would allow for mosaic analysis of gene function. We show that clonally related bacterium rods self-organize in a fractal growth pattern and can remain linked during colony development revealing a potential target against microbiota growth.

Mutability of demographic noise in microbial range expansions

Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.

Engineering pattern formation and morphogenesis

The development of natural tissues, organs and bodies depends on mechanisms of patterning and of morphogenesis, typically (but not invariably) in that order, and often several times at different final scales. Using synthetic biology to engineer patterning and morphogenesis will both enhance our basic understanding of how development works, and provide important technologies for advanced tissue engineering. Focusing on mammalian systems built to date, this review describes patterning systems, both contact-mediated and reaction-diffusion, and morphogenetic effectors. It also describes early attempts to connect the two to create self-organizing physical form. The review goes on to consider how these self-organized systems might be modified to increase the complexity and scale of the order they produce, and outlines some possible directions for future research and development.

The evolution of tit-for-tat in bacteria via the type VI secretion system

Tit-for-tat is a familiar principle from animal behavior: individuals respond in kind to being helped or harmed by others. Remarkably some bacteria appear to display tit-for-tat behavior, but how this evolved is not understood. Here we combine evolutionary game theory with agent-based modelling of bacterial tit-for-tat, whereby cells stab rivals with poisoned needles (the type VI secretion system) after being stabbed themselves. Our modelling shows tit-for-tat retaliation is a surprisingly poor evolutionary strategy, because tit-for-tat cells lack the first-strike advantage of preemptive attackers. However, if cells retaliate strongly and fire back multiple times, we find that reciprocation is highly effective. We test our predictions by competing Pseudomonas aeruginosa (a tit-for-tat species) with Vibrio cholerae (random-firing), revealing that P. aeruginosa does indeed fire multiple times per incoming attack. Our work suggests bacterial competition has led to a particular form of reciprocation, where the principle is that of strong retaliation, or 'tits-for-tat'.

Engineering and modeling of multicellular morphologies and patterns

Synthetic multicellular (MC) systems have the capacity to increase our understanding of biofilms and higher organisms, and to serve as engineering platforms for developing complex products in the areas of medicine, biosynthesis and smart materials. Here we provide an interdisciplinary perspective and review on emerging approaches to engineer and model MC systems. We lay out definitions for key terms in the field and identify toolboxes of standardized parts which can be combined into various MC algorithms to achieve specific outcomes. Many essential parts and algorithms have been demonstrated in some form. As key next milestones for the field, we foresee the improvement of these parts and their adaptation to more biological systems, the demonstration of more complex algorithms, the advancement of quantitative modeling approaches and compilers to support rational MC engineering, and implementation of MC engineering for practical applications.

Pattern Engineering of Living Bacterial Colonies Using Meniscus-Driven Fluidic Channels

Creating adaptive, sustainable, and dynamic biomaterials is a forthcoming mission of synthetic biology. Engineering spatially organized bacterial communities has a potential to develop such bio-metamaterials. However, generating living patterns with precision, robustness, and a low technical barrier remains as a challenge. Here we present an easily implementable technique for patterning live bacterial populations using a controlled meniscus-driven fluidics system, named as MeniFluidics. We demonstrate multiscale patterning of biofilm colonies and swarms with submillimeter resolution. Utilizing the faster bacterial spreading in liquid channels, MeniFluidics allows controlled bacterial colonies both in space and time to organize fluorescently labeled Bacillus subtilis strains into a converged pattern and to form dynamic vortex patterns in confined bacterial swarms. The robustness, accuracy, and low technical barrier of MeniFluidics offer a tool for advancing and inventing new living materials that can be combined with genetically engineered systems, and adding to fundamental research into ecological, evolutional, and physical interactions between microbes.

The evolution of the type VI secretion system as a disintegration weapon

The type VI secretion system (T6SS) is a nanomachine used by many bacteria to drive a toxin-laden needle into other bacterial cells. Although the potential to influence bacterial competition is clear, the fitness impacts of wielding a T6SS are not well understood. Here we present a new agent-based model that enables detailed study of the evolutionary costs and benefits of T6SS weaponry during competition with other bacteria. Our model identifies a key problem with the T6SS. Because of its short range, T6SS activity becomes self-limiting, as dead cells accumulate in its way, forming “corpse barriers” that block further attacks. However, further exploration with the model presented a solution to this problem: if injected toxins can quickly lyse target cells in addition to killing them, the T6SS becomes a much more effective weapon. We tested this prediction with single-cell analysis of combat between T6SS-wielding Acinetobacter baylyi and T6SS-sensitive Escherichia coli. As predicted, delivery of lytic toxins is highly effective, whereas nonlytic toxins leave large patches of E. coli alive. We then analyzed hundreds of bacterial species using published genomic data, which suggest that the great majority of T6SS-wielding species do indeed use lytic toxins, indicative of a general principle underlying weapon evolution. Our work suggests that, in the T6SS, bacteria have evolved a disintegration weapon whose effectiveness often rests upon the ability to break up competitors. Understanding the evolutionary function of bacterial weapons can help in the design of probiotics that can both establish well and eliminate problem species.

Bacteria attack each other with poison-tipped spears. This study combines theory and experiments to show that these spears (Type VI Secretion Systems) have evolved to break their targets apart with lytic toxins, as this then clears the way to rapidly stab new victims.

Phase variation of a signal transduction system controls Clostridioides difficile colony morphology, motility, and virulence

Recent work has revealed that Clostridioides difficile, a major cause of nosocomial diarrheal disease, exhibits phenotypic heterogeneity within a clonal population as a result of phase variation. Many C. difficile strains representing multiple ribotypes develop two colony morphotypes, termed rough and smooth, but the biological implications of this phenomenon have not been explored. Here, we examine the molecular basis and physiological relevance of the distinct colony morphotypes produced by this bacterium. We show that C. difficile reversibly differentiates into rough and smooth colony morphologies and that bacteria derived from the isolates display discrete motility behaviors. We identified an atypical phase-variable signal transduction system consisting of a histidine kinase and two response regulators, named herein colony morphology regulators RST (CmrRST), which mediates the switch in colony morphology and motility behaviors. The CmrRST-regulated surface motility is independent of flagella and type IV pili, suggesting a novel mechanism of cell migration in C. difficile. Microscopic analysis of cell and colony structure indicates that CmrRST promotes the formation of elongated bacteria arranged in bundled chains, which may contribute to bacterial migration on surfaces. In a hamster model of acute C. difficile disease, the CmrRST system is required for disease development. Furthermore, we provide evidence that CmrRST phase varies during infection, suggesting that the intestinal environment impacts the proportion of CmrRST-expressing C. difficile. Our findings indicate that C. difficile employs phase variation of the CmrRST signal transduction system to generate phenotypic heterogeneity during infection, with concomitant effects on bacterial physiology and pathogenesis.

Emergence of active nematics in chaining bacterial biofilms

Growing tissue and bacterial colonies are active matter systems where cell divisions and cellular motion generate active stress. Although they operate in the non-equilibrium regime, these biological systems can form large-scale ordered structures. How mechanical instabilities drive the dynamics of active matter systems and form ordered structures are not well understood. Here, we use chaining Bacillus subtilis, also known as a biofilm, to study the relation between mechanical instabilities and nematic ordering. We find that bacterial biofilms have intrinsic length scales above which a series of mechanical instabilities occur. Localized stress and friction drive buckling and edge instabilities which further create nematically aligned structures and topological defects. We also observe that topological defects control stress distribution and initiate the formation of sporulation sites by creating three-dimensional structures. In this study we propose an alternative active matter platform to study the essential roles of mechanics in growing biological tissue.