Bacteria clustering by polymers induces the expression of quorum sense controlled phenotypes

Bacteria deploy a range of chemistries to regulate their behaviour and respond to their environment. Quorum sensing is one mean by which bacteria use chemical reactions to modulate pre-infection behaviour such as surface attachment. Polymers that can interfere with bacterial adhesion or the chemical reactions used for quorum sensing are thus a potential means to control bacterial population responses. Here we report how polymeric "bacteria sequestrants", designed to bind to bacteria through electrostatic interactions and thus inhibit bacterial adhesion to surfaces, induce the expression of quorum sensing controlled phenotypes as a consequence of cell clustering. A combination of polymer and analytical chemistry, biological assays and computational modelling has been used to characterise the feedback between bacteria clustering and quorum sensing signaling. We have also derived design principles and chemical strategies for controlling bacterial behaviour at the population leve

An Approach to the Engineering of Cellular Models Based on P Systems

Living cells assembled into colonies or tissues communicate using complex systems. These systems consist in the interaction between many molecular species distributed over many compartments. Among the different cellular processes used by cells to monitor their environment and respond accordingly, gene regulatory networks, rather than individual genes, are responsible for the information processing and orchestration of the appropriate response [16]. In this respect, synthetic biology has emerged recently as a novel discipline aiming at unravelling the design principles in gene regulatory systems by synthetically engineering transcriptional networks which perform a specific and prefixed task [2]. Formal modelling and analysis are key methodologies used in the field to engineer, assess and compare different genetic designs or devices. In order to model cellular systems in colonies or tissues one requires a formalism able to represent the following relevant features: – Single cells should be described as the elementary units in the system. Nevertheless, they cannot be represented as homogeneous points as they exhibit complex structures containing different compartments where specific molecular species interact according to particular reactions. – The molecular interactions taking place in cellular systems are inherently discrete and stochastic processes. This is a key feature of cellular systems that needs to be taken into account when describing their dynamics [9]. – It has been postulated that gene regulatory networks are organised in a modular manner in such a way that cellular processes arise from the orchestrated interactions between different genetic transcriptional units that can be considered separable modules [1]. – Spatial and geometric information must be represented in the system in order to describe processes involving pattern formation. In this work we review recent advances in the use of the computational paradigm membrane computing or P systems as a formal methodology in synthetic biology for the specification and analysis on cellular system models according to the previously presented points

The cognitive cell: bacterial behavior reconsidered

Research on how bacteria adapt to changing environments underlies the contemporary biological understanding of signal transduction, and signal transduction provides the foundation of the information-processing approach that is the hallmark of the ‘cognitive revolution,’ which began in the mid-20th century. Yet cognitive scientists largely remain oblivious to research into microbial behavior that might provide insights into problems in their own domains, while microbiologists seem equally unaware of the potential importance of their work to understanding cognitive capacities in multicellular organisms, including vertebrates. Evidence in bacteria for capacities encompassed by the concept of cognition is reviewed. Parallels exist not only at the heuristic level of functional analogue, but also at the level of molecular mechanism, evolution and ecology, which is where fruitful cross-fertilization among disciplines might be found

Protein logic: a statistical mechanical study of signal integration at the single-molecule level

Information processing and decision making is based upon logic operations, which in cellular networks has been well characterized at the level of transcription. In recent years however, both experimentalists and theorists have begun to appreciate that cellular decision making can also be performed at the level of a single protein, giving rise to the notion of protein logic. Here we systematically explore protein logic using a well known statistical mechanical model. As an example system, we focus on receptors which bind either one or two ligands, and their associated dimers. Notably, we find that a single heterodimer can realize any of the 16 possible logic gates, including the XOR gate, by variation of biochemical parameters. We then introduce the novel idea that a set of receptors with fixed parameters can encode functionally unique logic gates simply by forming different dimeric combinations. An exhaustive search reveals that the simplest set of receptors (two single-ligand receptors and one double-ligand receptor) can realize several different groups of three unique gates, a result for which the parametric analysis of single receptors and dimers provides a clear interpretation. Both results underscore the surprising functional freedom readily available to cells at the single-protein level.Comment: 19 pages, 4 figures and 9 pages S

A Multiscale Modeling Framework Based on P Systems

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems. The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems. In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems. The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.Kingdom's Engineering and Physical Sciences Research Council EP/ E017215/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/F01855X/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/D019613/

A Multiscale Modeling Framework Based on P Systems

Cellular systems present a highly complex organization at different scales including the molecular, cellular and colony levels. The complexity at each one of these levels is tightly interrelated. Integrative systems biology aims to obtain a deeper understanding of cellular systems by focusing on the systemic and systematic integration of the different levels of organization in cellular systems. The different approaches in cellular modeling within systems biology have been classified into mathematical and computational frameworks. Specifically, the methodology to develop computational models has been recently called executable biology since it produces executable algorithms whose computations resemble the evolution of cellular systems. In this work we present P systems as a multiscale modeling framework within executable biology. P system models explicitly specify the molecular, cellular and colony levels in cellular systems in a relevant and understandable manner. Molecular species and their structure are represented by objects or strings, compartmentalization is described using membrane structures and finally cellular colonies and tissues are modeled as a collection of interacting individual P systems. The interactions between the components of cellular systems are described using rewriting rules. These rules can in turn be grouped together into modules to characterize specific cellular processes. One of our current research lines focuses on the design of cell systems biology models exhibiting a prefixed behavior through the automatic assembly of these cellular modules. Our approach is equally applicable to synthetic as well as systems biology.Kingdom's Engineering and Physical Sciences Research Council EP/ E017215/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/F01855X/1Biotechnology and Biological Sciences Research Council/United Kingdom BB/D019613/

Integrating perspectives in actinomycete research: an ActinoBase review of 2020-21

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: i) technology and methodology; ii) specialised metabolites; iii) development and regulation; and iv) ecology and host interactions

Iron metabolism at the interface between host and pathogen: From nutritional immunity to antibacterial development

Nutritional immunity is a form of innate immunity widespread in both vertebrates and invertebrates. The term refers to a rich repertoire of mechanisms set up by the host to inhibit bacterial proliferation by sequestering trace minerals (mainly iron, but also zinc and manganese). This strategy, selected by evolution, represents an effective front-line defense against pathogens and has thus inspired the exploitation of iron restriction in the development of innovative antimicrobials or enhancers of antimicrobial therapy. This review focuses on the mechanisms of nutritional immunity, the strategies adopted by opportunistic human pathogen Staphylococcus aureus to circumvent it, and the impact of deletion mutants on the fitness, infectivity, and persistence inside the host. This information finally converges in an overview of the current development of inhibitors targeting the different stages of iron uptake, an as-yet unexploited target in the field of antistaphylococcal drug discovery