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Goni-Moreno, A.

Publications and source records attributed to Goni-Moreno, A..

16 recordsLinked to original sources
bioRxiv2025

Growth control as a central regulator for tuning the cellular context

The cellular context interacts with genetic circuits, decisively defining their performance. However, contextual dependencies (the interplay between the host and the circuit) are often difficult to engineer rationally, leading to a lack of control over circuit behaviour. To address this challenge, we replaced the native regulatory machinery of the RNA polymerase (RNAP), the cells core protein-making machine, from the bacteria Pseudomonas putida KT2440 with an inducible system, enabling tunable growth regulation and thereby gaining systemic control over the entire cellular machinery. Specifically, this was achieved by placing key components, the {beta} and {beta} subunits of the enzyme, under the control of the XylS-Pm inducible system. By using its cognate chemical inducer, 3-methylbenzoate, cells growth can be controlled at will, enabling the precise tuning of the cellular context into distinct, stable states. We correlated genetic circuit behaviour with the cells growth state by observing the constitutive expression of a reporter gene and the performance of a collection of genetic NOT logic gates. Our results show that the modulation of contextual dependencies is specific to the circuit components but not a random process. A mathematical model allowed us to classify that modulation into three different categories for our library of NOT gates, based on the prediction of how RNAP availability shapes host-circuit interaction. Finally, using growth control as an input for a 2-input circuit lead to a NAND gate with the potential for morphological computing, where the cells physical body itself undertakes part of the information processing. Our findings indicate that growth control can be used as an engineering parameter, allowing us to search for optimal scenarios that enhance the potential of genetic tools.

synthetic biology↗
bioRxiv2024

Building a syntrophic Pseudomonas putida consortium with reciprocal substrate processing of lignocellulosic disaccharides

Synthetic microbial consortia can leverage their expanded enzymatic reach to tackle biotechnological challenges too complex for single strains, such as lignocellulose valorisation. The benefit of metabolic cooperation comes with a catch - installing stable interactions between consortium members. We constructed a syntrophic consortium of Pseudomonas putida strains for lignocellulosic disaccharide processing. Two strains were engineered to hydrolyse and metabolise lignocellulosic sugars: one grows on xylose and hydrolyses cellobiose to produce glucose, while the other grows on glucose and cleaves xylobiose to produce xylose. This specialisation allows each strain to provide essential growth substrate to its partner, establishing a stable mutualistic interaction, which we term reciprocal substrate processing. Key enzymes from Escherichia coli (xylose isomerase pathway) and Thermobifida fusca (glycoside hydrolases) were introduced into P. putida to broaden its carbohydrate utilisation capabilities and arranged in a way to install the strain cross-dependency. A mathematical model of the consortium assisted in predicting the effects of substrate composition, strain ratios, and protein expression levels on population dynamics. Our results demonstrated that modulating extrinsic factors such as substrate concentration can optimise growth and balance fitness disparities between the strains, but achieving this by altering intrinsic factors such as glycoside hydrolase expression levels is much more challenging. This study underscores the potential of synthetic microbial consortia to facilitate the bioconversion of lignocellulosic sugars and offers insights into overcoming the challenges of establishing synthetic microbial cooperation.

synthetic biology↗
bioRxiv2024

Dynamics of genetic circuits in Pseudomonas protegens

The engineering of genetic circuits to perform predefined computations is central to synthetic biology, enabling living cells with new functionalities applicable across various domains. However, these circuits are often specifically tailored to particular cellular hosts, with Escherichia coli being the most popular. Consequently, their intended functions may not translate well to other organisms, limiting their scope. Understanding circuit dynamics in less familiar organisms is crucial, especially for niche-specific applications requiring cellular chassis different from model organisms generally used in synthetic biology. Here, we develop a combined experimental and theoretical pipeline to evaluate the performance of NOT logic circuits, also called inverters, in the soil bacterium Pseudomonas protegens Pf-5--a host renowned for its unique environmental functions and a newcomer to genetic circuitry. Inverters were experimentally tested to characterize input-output functionality, and mathematical modelling was used to infer the dynamic principles of circuit modules. The model quantified the individual impacts of key parameters--such as translation efficiency, repressor performance, and promoter activity--on output levels, enabling predictions about inter-host circuit portability. This parameter calibration revealed unique properties of the chassis, including faster transitions between on and off circuit states compared to the synthetic biology workhorse Pseudomonas putida. These characteristics may reflect adaptations to the fluctuating conditions of the plant rhizosphere, where this bacteria thrives. As a result, our work provides DNA parts, circuits and mathematical characterizations to establish P. protegens Pf-5 as a viable chassis for environmental synthetic biology.

synthetic biology↗
bioRxiv2024

Genetic designs for stochastic and probabilistic biocomputing

The programming of computations in living cells can be done by manipulating information flows within genetic networks. Typically, a single bit of information is encoded by a single genes steady state expression. Expression is discretized into high and low levels that correspond to 0 and 1 logic values, analogous to the high and low voltages in electronic logic circuits. However, the processes of molecular signaling and computation in living systems challenge this computational paradigm with their dynamic, stochastic and continuous operation. Although there is a good understanding of these phenomena in genetic networks, and there are already stochastic and probabilistic models of computation which can take on these challenges, there is currently a lack of work which puts both together to implement computations tailored to these features of living matter. Here, we design genetic networks for stochastic and probabilistic computing paradigms and develop the theory behind their operation. Moving beyond the digital abstraction, we explore the concepts of bit-streams (sequences of pulses acting as time-based signals) and probabilistic-bits or p-bits (values that can be either 1 or 0 with an assigned probability), as more suitable candidates for the encoding and processing of information in genetic networks. Specifically, the conceptualization of signals as stochastic bit-streams allows for encoding information in the frequency of random expression pulses, offering advantages such as robustness to noise. Additionally, the notion of p-bit enables the design of genetic circuits with capabilities surpassing those of current genetic logic gates, including invertibility. We design several circuits to illustrate these advantages and provide mathematical models and computational simulations that demonstrate their functionality. Our approach to stochastic and probabilistic computing in living cells not only enhances and reflects understanding of information processing in biological systems but also presents promising avenues for designing genetic circuits with advanced functionalities.

synthetic biology↗
bioRxiv2024

Reprogramming genetic circuits using space

Genetic circuits confer computing abilities to living cells, performing novel transformations of input stimuli into output responses. Circuit editing often focuses on substituting DNA components, such as RBSs, regulators, or promoters, from part libraries to achieve desired performance. However, this approach is inherently limited by the availability of DNA components. Here, we show that circuit performance can be reprogrammed without altering its DNA sequence by using a library of positions: a set of physical locations within the cells volume. Using bacteria as the living chassis, we engineer 219 spatially unique genetic circuits of four different types--three regulatory cascades and a toggle switch--by either inserting the entire circuit in a specific chromosomal position or separating and distributing circuit modules. Their analysis, together with a mathematical model, reveals that spatial positioning can be used not only to optimize circuits but also to switch circuits between modes of operation, giving rise to new functions as circuit complexity increases. We provide foundational insights into leveraging intracellular space for circuit design.

synthetic biology↗
bioRxiv2022

An electrogenetic toggle switch design

Synthetic biology uses molecular biology to implement genetic circuits that perform computations. These circuits can process inputs and deliver outputs according to predefined rules that are encoded, often entirely, into genetic parts. However, the field has recently begun to focus on using mechanisms beyond the realm of genetic parts for engineering biological circuits. We analyse the use of electrogenic processes for circuit design and present a model for a merged genetic and electrogenetic toggle switch. Computational simulations explore conditions under which bistability emerges in order to identify the circuit design principles for best switch performance. The results provide a basis for the rational design and implementation of hybrid devices that can be measured and controlled both genetically and electronically.

synthetic biology↗
bioRxiv2021

Network visualisation of synthetic biology designs

As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information.

synthetic biology↗
bioRxiv2020

The subcellular architecture of the xyl gene expression flow of the TOL catabolic plasmid of Pseudomonas putida mt-2

Despite intensive research on the biochemical and regulatory features of the archetypal catabolic TOL system borne by pWW0 of Pseudomonas putida mt-2, the physical arrangement and tridimensional logic of the xyl gene expression flow remains unknown. In this work, the spatial distribution of specific xyl mRNAs with respect to the host nucleoid, the TOL plasmid and the ribosomal pool has been investigated. In situ hybridization of target transcripts with fluorescent oligonucleotide probes revealed that xyl mRNAs cluster in discrete foci, adjacent but clearly separated from the TOL plasmid and the cell nucleoid. Also, they co-localize with ribosome-rich domains of the intracellular milieu. This arrangement was kept even when the xyl genes were artificially relocated at different chromosomal locations. The same happened when genes were expressed through a heterologous T7 polymerase-based system, which originated mRNA foci outside the DNA. In contrast, rifampicin treatment, known to ease crowding, blurred the confinement of xyl transcripts. This suggested that xyl mRNAs intrinsically run away from their initiation sites to ribosome-rich points for translation--rather than being translated coupled to transcription. Moreover, the results suggest that the distinct subcellular motion of xyl mRNAs results both from innate properties of the sequence at stake and the physical forces that keep the ribosomal pool away from the nucleoid in P. putida. This scenario is discussed on the background of current knowledge on the 3D organization of the gene expression flow in other bacteria and the environmental lifestyle of this soil microorganism. IMPORTANCEThe transfer of information between DNA, RNA and proteins in a bacterium is often compared to the decoding of a piece of software in a computer. However, the tridimensional layout and the relational logic of the cognate biological hardware i.e. the nucleoid, the RNA polymerase and the ribosomes, are habitually taken for granted. In this work we inspected the localization and fate of the transcripts that stem from the archetypal biodegradative plasmid pWW0 of soil bacterium Pseudomonas putida KT2440 through the non-homogenous milieu of the bacterial cytoplasm. The results expose that-- similarly to computers also--the material components that enable the expression flow are well separated physically and they decipher the sequences through a distinct tridimensional arrangement with no indication of transcription/translation coupling. We argue that the resulting subcellular architecture enters an extra regulatory layer that obeys a species-specific positional code that accompanies the environmental lifestyle of this bacterium.

microbiology↗
bioRxiv2020

FlowScatt: enabling volume-independent flow cytometry data by decoupling fluorescence from scattering

MotivationMeasuring fluorescence by flow cytometry is fundamental for characterising single-cell performance. While it is known that fluorescence and scattering values tend to positively correlate, the impact of cell volume on fluorescence is typically overlooked. This makes of fluorescence values alone an inaccurate measurement for high-precision characterisations. ResultsWe developed FlowScatt, an open-source software package that removes volume-dependency in the fluorescence channel. Using FlowScatt, flourescence values are re-calculated based on the unified volume per cell that arises from scattering decomposition. AvailabilityFlowScatt is openly available as a Python package on https://github.com/rstoof/FlowScatt. Experimental data for validation is available online. Contactangel.goni-moreno@newcastle.ac.uk

bioinformatics↗
bioRxiv2020

A standardized broad host range inverter package for genetic circuitry design in Gram-negative bacteria

Genetically encoded logic gates, especially inverters--NOT gates--are the building blocks for designing circuits, engineering biosensors or decision-making devices in synthetic biology. However, the repertoire of inverters readily available for different species is rather limited. In this work, a large whole of NOT gates that was shown to function previously in a specific strain of Escherichia coli, was recreated as broad host range (BHR) collection of constructs assembled in low, medium and high copy number plasmid backbones of the SEVA (Standard European Vector Architecture) collection. The input/output function of each of the gates was characterized and parameterized in the environmental bacterium and metabolic engineering chassis Pseudomonas putida. Comparisons of the resulting fluorescence cytometry data with those published for the same gates in Escherichia coli provided useful hints on the portability of the corresponding gates. The hereby described BHR inverter package (20 different versions of 12 distinct gates) thus becomes a toolbox of choice for designing genetic circuitries in a variety of Gram-negative species other than E. coli.

synthetic biology↗
bioRxiv2020

Contextual dependencies expand the re-usability of genetic inverters

The design and implementation of Boolean logic functions in living cells has become a very active field within synthetic biology. By controlling networks of regulatory proteins, novel genetic circuits are engineered to generate predefined output responses. Although many current implementations focus solely on the genetic components of the circuit, the host context in which the circuit performs is crucial for its outcome. Here, we characterise 20 genetic NOT logic gates (inverters) in up to 7 bacterial-based contexts each, to finally generate 135 different functions. The contexts we focus on are particular combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each NOT logic gate shows seven different logic behaviours, depending on the context. That is, gates can be reconfigured to fit response requirements by changing only contextual parameters. Computational analysis shows that this range of behaviours improves the compatibility between gates, because there are considerably more possibilities for combination than when considering a unique function per genetic construct. Finally, we address the issue of interoperability and portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expand the scope of the functions that can be engineered in complex cellular environments, and advocate for considering context as a fundamental design parameter for synthetic biology.

synthetic biology↗
bioRxiv2019

Digitalizing heterologous gene expression in Gram-negative bacteria with a portable on/off module

While prokaryotic promoters controlled by signal-responding regulators typically display a range of input/output ratios when exposed to cognate inducers, virtually no naturally occurring cases are known to have an off state of zero transcription--as ideally needed for synthetic circuits. To overcome this problem we have modelled and implemented simple digitalizer module that completely suppresses the basal level of otherwise strong promoters in such a way that expression in the absence of induction is entirely impeded. The circuit involves the interplay of a translation-inhibitory sRNA with the translational coupling of the gene of interest to a repressor such as LacI. The digitalizer module was validated with the strong inducible promoters Pm (induced by XylS in the presence of benzoate) and PalkB (induced by AlkS/dicyclopropylketone) and shown to perform effectively both in E. coli and the soil bacterium Pseudomonas putida. The distinct expression architecture allowed cloning and conditional expression of e.g. colicin E3, one molecule of which per cell suffices to kill the host bacterium. Revertants that escaped ColE3 killing were not found in hosts devoid of insertion sequences, suggesting that mobile elements are a major source of circuit inactivation in vivo.

synthetic biology↗
bioRxiv2019

A model for the spatio-temporal design of gene regulatory circuits

The design of increasingly complex gene regulatory networks relies upon mathematical modelling to link the gap that goes from conceptualisation to implementation. An overarching challenge is to update modelling abstractions and assumptions as new mechanistic information arises. Although models of bacterial gene regulation are often based on the assumption that the role played by intracellular physical distances between genetic elements is negligible, it has been shown that bacteria are highly ordered organisms, compartmentalizing their vital functions in both time and space. Here, we analysed the dynamical properties of regulatory interactions by explicitly modelling spatial constraints. Key to the model is the combined search by a regulator for its target promoter via 1D sliding along the chromosome and 3D diffusion through the cytoplasm. Moreover, this search was coupled to gene expression dynamics, with special attention to transcription factor-promoter interplay. As a result, promoter activity within the model depends on its physical separation from the regulator source. Simulations showed that by modulating the distance between DNA components in the chromosome, output levels changed accordingly. Finally, previous experimental results with engineered bacteria in which this distance was minimized or enlarged were successfully reproduced by the model. This suggests that the spatial specification of the circuit alone can be exploited as a design parameter to select programmable output levels.

synthetic biology↗
bioRxiv2018

SBOL-OWL: An ontological approach for formal and semantic representation of synthetic genetic circuits

Standard representation of data is key for the reproducibility of designs in synthetic biology. The Synthetic Biology Open Language (SBOL) has already emerged as a data standard to represent genetic circuit designs, and it is based on capturing data using graphs. The language provides the syntax using a free text document which is accessible to humans only. Here, we provide SBOL-OWL, an ontology for a machine understandable definition of SBOL. This ontology acts as a semantic layer for genetic circuit designs. As a result, computational tools can understand the meaning of design entities in addition to parsing structured SBOL data. SBOL-OWL not only describes how genetic circuits can be constructed computationally, it also facilitates the use of several existing Semantic Web tooling for synthetic biology. Here, we demonstrate some of these features, for example, to validate designs and check for inconsistencies. Through the use of SBOL-OWL, queries are simplified and become more intuitive. Moreover, existing reasoners can be used to infer information about genetic circuit designs that cant be directly retrieved using existing querying mechanisms. This ontological representation of the SBOL standard provides a new perspective to the verification, representation and querying of information about synthetic genetic circuits and is important to incorporate complex design information via the integration of biological ontologies.

synthetic biology↗
bioRxiv2018

Dynamical Task Switching in Cellular Computers

We present a scheme for implementing a version of task switching in engineered bacteria, based on the manipulation of plasmid copy numbers. Our method allows for the embeddingof multiple computations in a cellular population, whilst minimising resource usage inefficiency. We describe the results of computational simulations of our model, and discuss the potential for future work in this area.

synthetic biology↗
bioRxiv2018

Capturing Multicellular System Designs Using the Synthetic Biology Open Language (SBOL)

Synthetic biology aims to improve the development of biological systems and in-crease their reproducibility through the use of engineering principles, such as stan-dardisation and modularisation. It is important that these systems can be represented and shared in a standard way to ensure they are easily understood, reproduced, and utilised by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterisation. Thus far, this standard has been used to represent designs in homogeneous systems, where the same design is implemented in every cell. In recent years there has been increasing interest in multicellular systems, where biological designs are split across multiple cells to optimise the system behaviour and function. Here we show how the SBOL standard can be used to represent such multicellular systems, and hence how researchers can better share designs with the community.

synthetic biology↗