Angel Goñi-Moreno

SEVA 2.0: an update of the Standard European Vector Architecture for de-/re-construction of bacterial functionalities

The Standard European Vector Architecture 2.0 database (SEVA-DB 2.0, http://seva.cnb.csic.es) is an improved and expanded version of the platform released in 2013 (doi: 10.1093/nar/gks1119) aimed at assisting the choice of optimal genetic tools for de-constructing and re-constructing complex prokaryotic phenotypes. By adopting simple compositional rules, the SEVA standard facilitates combinations of functional DNA segments that ease both the analysis and the engineering of diverse Gram-negative bacteria for fundamental or biotechnological purposes. The large number of users of the SEVA-DB during its first two years of existence has resulted in a valuable feedback that we have exploited for fixing DNA sequence errors, improving the nomenclature of the SEVA plasmids, expanding the vector collection, adding new features to the web interface and encouraging contributions of materials from the community of users. The SEVA platform is also adopting the Synthetic Biology Open Language (SBOL) for electronic-like description of the constructs available in the collection and their interfacing with genetic devices developed by other Synthetic Biology communities. We advocate the SEVA format as one interim asset for the ongoing transition of genetic design of microorganisms from being a trial-and-error endeavor to become an authentic engineering discipline.

Multicellular Computing Using Conjugation for Wiring

Recent efforts in synthetic biology have focussed on the implementation of logical functions within living cells. One aim is to facilitate both internal “re-programming” and external control of cells, with potential applications in a wide range of domains. However, fundamental limitations on the degree to which single cells may be re-engineered have led to a growth of interest in multicellular systems, in which a “computation” is distributed over a number of different cell types, in a manner analogous to modern computer networks. Within this model, individual cell type perform specific sub-tasks, the results of which are then communicated to other cell types for further processing. The manner in which outputs are communicated is therefore of great significance to the overall success of such a scheme. Previous experiments in distributed cellular computation have used global communication schemes, such as quorum sensing (QS), to implement the “wiring” between cell types. While useful, this method lacks specificity, and limits the amount of information that may be transferred at any one time. We propose an alternative scheme, based on specific cell-cell conjugation. This mechanism allows for the direct transfer of genetic information between bacteria, via circular DNA strands known as plasmids. We design a multi-cellular population that is able to compute, in a distributed fashion, a Boolean XOR function. Through this, we describe a general scheme for distributed logic that works by mixing different strains in a single population; this constitutes an important advantage of our novel approach. Importantly, the amount of genetic information exchanged through conjugation is significantly higher than the amount possible through QS-based communication. We provide full computational modelling and simulation results, using deterministic, stochastic and spatially-explicit methods. These simulations explore the behaviour of one possible conjugation-wired cellular computing system under different conditions, and provide baseline information for future laboratory implementations.

A reconfigurable NAND/NOR genetic logic gate

BackgroundEngineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations.ResultsWe describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs.ConclusionsWe present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

The Glycerol-Dependent Metabolic Persistence of Pseudomonas putida KT2440 Reflects the Regulatory Logic of the GlpR Repressor

ABSTRACT The growth of the soil bacterium Pseudomonas putida KT2440 on glycerol as the sole carbon source is characterized by a prolonged lag phase, not observed with other carbon substrates. We examined the bacterial growth in glycerol cultures while monitoring the metabolic activity of individual cells. Fluorescence microscopy and flow cytometry, as well as the analysis of the temporal start of growth in single-cell cultures, revealed that adoption of a glycerol-metabolizing regime was not the result of a gradual change in the whole population but rather reflected a time-dependent bimodal switch between metabolically inactive (i.e., nongrowing) and fully active (i.e., growing) bacteria. A transcriptional Φ(glpD-gfp) fusion (a proxy of the glycerol-3-phosphate [G3P] dehydrogenase activity) linked the macroscopic phenotype to the expression of the glp genes. Either deleting glpR (encoding the G3P-responsive transcriptional repressor that controls the expression of the glpFKRD gene cluster) or altering G3P formation (by overexpressing glpK, encoding glycerol kinase) abolished the bimodal glpD expression. These manipulations eliminated the stochastic growth start by shortening the otherwise long lag phase. Provision of glpR in trans restored the phenotypes lost in the ΔglpR mutant. The prolonged nongrowth regime of P. putida on glycerol could thus be traced to the regulatory device controlling the transcription of the glp genes. Since the physiological agonist of GlpR is G3P, the arrangement of metabolic and regulatory components at this checkpoint merges a positive feedback loop with a nonlinear transcriptional response, a layout fostering the observed time-dependent shift between two alternative physiological states. IMPORTANCE Phenotypic variation is a widespread attribute of prokaryotes that leads, inter alia, to the emergence of persistent bacteria, i.e., live but nongrowing members within a genetically clonal population. Persistence allows a fraction of cells to avoid the killing caused by conditions or agents that destroy most growing bacteria (e.g., some antibiotics). Known molecular mechanisms underlying the phenomenon include genetic changes, epigenetic variations, and feedback-based multistability. We show that a prolonged nongrowing state of the bacterial population can be brought about by a distinct regulatory architecture of metabolic genes when cells face specific nutrients (e.g., glycerol). Pseudomonas putida may have adopted the resulting carbon source-dependent metabolic bet hedging as an advantageous trait for exploring new chemical and nutritional landscapes. Defeating such naturally occurring adaptive features of environmental bacteria is instrumental in improving the performance of these microorganisms as whole-cell catalysts in a bioreactor setup. Phenotypic variation is a widespread attribute of prokaryotes that leads, inter alia, to the emergence of persistent bacteria, i.e., live but nongrowing members within a genetically clonal population. Persistence allows a fraction of cells to avoid the killing caused by conditions or agents that destroy most growing bacteria (e.g., some antibiotics). Known molecular mechanisms underlying the phenomenon include genetic changes, epigenetic variations, and feedback-based multistability. We show that a prolonged nongrowing state of the bacterial population can be brought about by a distinct regulatory architecture of metabolic genes when cells face specific nutrients (e.g., glycerol). Pseudomonas putida may have adopted the resulting carbon source-dependent metabolic bet hedging as an advantageous trait for exploring new chemical and nutritional landscapes. Defeating such naturally occurring adaptive features of environmental bacteria is instrumental in improving the performance of these microorganisms as whole-cell catalysts in a bioreactor setup.

Continuous computation in engineered gene circuits

In this paper we consider the problem of representation and measurement in genetic circuits, and investigate how they can affect the reliability of engineered systems. We propose a design scheme, based on the notion of continuous computation, which addresses these issues. We illustrate the methodology by showing how a concept from computer architecture (namely, branch prediction) may be implemented in vivo, using a distributed approach. Simulation results confirm the in-principle feasibility of our method, and offer valuable insights into its future laboratory validation.

Biocircuit design through engineering bacterial logic gates

Designing synthetic biocircuits to perform desired purposes is a scientific field that has exponentially grown over the past decade. The advances in genome sequencing, bacteria gene regulatory networks, as well as the further knowledge of intraspecies bacterial communication through quorum sensing signals are the starting point for this work. Although biocircuits are mostly developed in a single cell, here we propose a model in which every bacterium is considered to be a single logic gate and chemical cell-to-cell connections are engineered to control circuit function. Having one genetically modified bacterial strain per logic process would allow us to develop circuits with different behaviors by mixing the populations instead of re-programming the whole genetic network within a single strain. Two principal advantages of this procedure are highlighted. First, the fully connected circuits obtained where every cellgate is able to communicate with all the rest. Second, the resistance to the noise produced by inappropriate gene expression. This last goal is achieved by modeling thresholds for input signals. Thus, if the concentration of input does not exceed the threshold, it is ignored by the logic function of the gate.

Model for a population-based microbial oscillator.

Genetic oscillators are a major theme of interest in the emerging field of synthetic biology. Until recently, most work has been carried out using intra-cellular oscillators, but this approach restricts the broader applicability of such systems. Motivated by a desire to develop large-scale, spatially distributed cell-based computational systems, we present an initial design for a population-level oscillator which uses three different bacterial strains. Our system is based on the client-server model familiar to computer science, and uses quorum sensing for communication between nodes. Importantly, it is robust to perturbation and noise. We present the results of extensive in silico simulation tests, which confirm the feasibility of our design.

Cell differentiation defines acute and chronic infection cell types in Staphylococcus aureus

A central question to biology is how pathogenic bacteria initiate acute or chronic infections. Here we describe a genetic program for cell-fate decision in the opportunistic human pathogen Staphylococcus aureus, which generates the phenotypic bifurcation of the cells into two genetically identical but different cell types during the course of an infection. Whereas one cell type promotes the formation of biofilms that contribute to chronic infections, the second type is planktonic and produces the toxins that contribute to acute bacteremia. We identified a bimodal switch in the agr quorum sensing system that antagonistically regulates the differentiation of these two physiologically distinct cell types. We found that extracellular signals affect the behavior of the agr bimodal switch and modify the size of the specialized subpopulations in specific colonization niches. For instance, magnesium-enriched colonization niches causes magnesium binding to S. aureusteichoic acids and increases bacterial cell wall rigidity. This signal triggers a genetic program that ultimately downregulates the agr bimodal switch. Colonization niches with different magnesium concentrations influence the bimodal system activity, which defines a distinct ratio between these subpopulations; this in turn leads to distinct infection outcomes in vitro and in an in vivo murine infection model. Cell differentiation generates physiological heterogeneity in clonal bacterial infections and helps to determine the distinct infection types.

Deconvolution of gene expression noise into spatial dynamics of transcription factor-promoter interplay

Gene expression noise is not only the mere consequence of stochasticity, but also a signal that reflects the upstream physical dynamics of the cognate molecular machinery. Soil bacteria facing recalcitrant pollutants exploit noise of catabolic promoters to deploy beneficial phenotypes such as metabolic bet-hedging and/or division of biochemical labor. Although the role of upstream promoter-regulator interplay in the origin of this noise is little understood, its specifications are probably ciphered in flow cytometry data patterns. We studied Pm promoter activity of the environmental bacterium Pseudomonas putida and its cognate regulator XylS by following expression of Pm-gfp fusions in single cells. Using mathematical modeling and computational simulations, we determined the kinetic properties of the system and used them as a baseline code to interpret promoter activity in terms of upstream regulator dynamics. Transcriptional noise was predicted to depend on the intracellular physical distance between regulator source (where XylS is produced) and the target promoter. Experiments with engineered bacteria in which this distance is minimized or enlarged confirmed the predicted effects of source/target proximity on noise patterns. This approach allowed deconvolution of cytometry data into mechanistic information on gene expression flow. It also provided a basis for selecting programmable noise levels in synthetic regulatory circuits.

A Metabolic Widget Adjusts the Phosphoenolpyruvate-Dependent Fructose Influx in Pseudomonas putida

The regulatory nodes that govern metabolic traffic in bacteria often show connectivities that could be deemed unnecessarily complex at a first glance. Being a soil dweller and plant colonizer, Pseudomonas putida frequently encounters fructose in the niches that it inhabits. As is the case with many other sugars, fructose is internalized by a dedicated phosphoenolpyruvate (PEP)-dependent transport system (PTSFru), the expression of which is repressed by the fructose-1-P-responding Cra regulatory protein. However, Cra also controls a glyceraldehyde-3-P dehydrogenase that fosters accumulation of PEP (i.e., the metabolic fuel for PTSFru). A simple model representing this metabolic and regulatory device revealed that such an unexpected connectivity allows cells to shift smoothly between fructose-rich and fructose-poor conditions. Therefore, although the metabolic networks that handle sugar (i.e., fructose) consumption look very similar in most eubacteria, the way in which their components are intertwined endows given microorganisms with emergent properties for meeting species-specific and niche-specific needs. ABSTRACT Fructose uptake in the soil bacterium Pseudomonas putida occurs through a canonical phosphoenolpyruvate (PEP)-dependent sugar transport system (PTSFru). The logic of the genetic circuit that rules its functioning is puzzling: the transcription of the fruBKA operon, encoding all the components of PTSFru, can escape the repression exerted by the catabolite repressor/activator protein Cra solely in the presence of intracellular fructose-1-P, an agonist formed only when fructose has been already transported. To study this apparently incongruous regulatory architecture, the changes in the transcriptome brought about by a seamless Δcra deletion in P. putida strain KT2440 were inspected under different culture conditions. The few genes found to be upregulated in the cra mutant unexpectedly included PP_3443, encoding a bona fide glyceraldehyde-3-P dehydrogenase. An in silico model was developed to explore emergent properties that could result from such connections between sugar uptake with Cra and PEP. Simulation of fructose transport revealed that sugar uptake called for an extra supply of PEP (obtained through the activity of PP_3443) that was kept (i.e., memorized) even when the carbohydrate disappeared from the medium. This feature was traced to the action of two sequential inverters that connect the availability of exogenous fructose to intracellular PEP levels via Cra/PP_3443. The loss of such memory caused a much longer lag phase in cells shifted from one growth condition to another. The term “metabolic widget” is proposed to describe a merged biochemical and regulatory patch that tailors a given node of the cell molecular network to suit species-specific physiological needs. IMPORTANCE The regulatory nodes that govern metabolic traffic in bacteria often show connectivities that could be deemed unnecessarily complex at a first glance. Being a soil dweller and plant colonizer, Pseudomonas putida frequently encounters fructose in the niches that it inhabits. As is the case with many other sugars, fructose is internalized by a dedicated phosphoenolpyruvate (PEP)-dependent transport system (PTSFru), the expression of which is repressed by the fructose-1-P-responding Cra regulatory protein. However, Cra also controls a glyceraldehyde-3-P dehydrogenase that fosters accumulation of PEP (i.e., the metabolic fuel for PTSFru). A simple model representing this metabolic and regulatory device revealed that such an unexpected connectivity allows cells to shift smoothly between fructose-rich and fructose-poor conditions. Therefore, although the metabolic networks that handle sugar (i.e., fructose) consumption look very similar in most eubacteria, the way in which their components are intertwined endows given microorganisms with emergent properties for meeting species-specific and niche-specific needs.