Ultrasensitivity by molecular titration in spatially propagating enzymatic reactions

Chemical waves in reaction-diffusion networks of small organic molecules

Chemical waves represent one of the fundamental behaviors that emerge in nonlinear, out-of-equilibrium chemical systems. They also play a central role in regulating behaviors and development of biological organisms. Nevertheless, understanding their properties and achieving their rational synthesis remains challenging. In this work, we obtained traveling chemical waves using synthetic organic molecules. To accomplish this, we ran a thiol-based reaction network in an unstirred flow reactor. Our observations revealed single or multiple waves moving in either the same or opposite directions, a behavior controlled by the geometry of our reactor. A numerical model can fully reproduce this behavior using the proposed reaction network. To better understand the formation of waves, we varied the diffusion coefficient of the fast inhibitor component of the reaction network by attaching polyethylene glycol tails with different lengths to maleimide and studied how these changes affect the properties of the waves and conditions for their sustained production. These studies point towards the importance of the molecular titration network motif in controlling the production of chemical waves in this system. Furthermore, we used machine learning (ML) tools to identify phase boundaries for classes of dynamic behaviors of this system, thus demonstrating the applicability of ML tools for the study of experimental nonlinear reaction-diffusion systems.

Computing Arithmetic Functions Using Immobilised Enzymatic Reaction Networks

Living systems use enzymatic reaction networks to process biochemical information and make decisions in response to external or internal stimuli. Herein, we present a modular and reusable platform for molecular information processing using enzymes immobilised in hydrogel beads and compartmentalised in a continuous stirred tank reactor. We demonstrate how this setup allows us to perform simple arithmetic operations, such as addition, subtraction and multiplication, using various concentrations of substrates or inhibitors as inputs and the production of a fluorescent molecule as the readout.

Reaction–Diffusion Patterning of DNA-Based Artificial Cells

Biological cells display complex internal architectures with distinct micro environments that establish the chemical heterogeneity needed to sustain cellular functions. The continued efforts to create advanced cell mimics, namely, artificial cells, demands strategies for constructing similarly heterogeneous structures with localized functionalities. Here, we introduce a platform for constructing membraneless artificial cells from the self-assembly of synthetic DNA nanostructures in which internal domains can be established thanks to prescribed reaction–diffusion waves. The method, rationalized through numerical modeling, enables the formation of up to five distinct concentric environments in which functional moieties can be localized. As a proof-of-concept, we apply this platform to build DNA-based artificial cells in which a prototypical nucleus synthesizes fluorescent RNA aptamers that then accumulate in a surrounding storage shell, thus demonstrating the spatial segregation of functionalities reminiscent of that observed in biological cells.

Spatiotemporal Regulation of Hydrogel Actuators by Autocatalytic Reaction Networks

Regulating hydrogel actuators with chemical reaction networks is instrumental for constructing life-inspired smart materials. Herein, hydrogel actuators are engineered that are regulated by the autocatalytic front of thiols. The actuators consist of two layers. The first layer, which is regular polyacrylamide hydrogel, is in a strained conformation. The second layer, which is polyacrylamide hydrogel with disulfide crosslinks, maintains strain in the first layer. When thiols released by the autocatalytic front reduce disulfide crosslinks, the hydrogel actuates by releasing the mechanical strain in the first layer. The autocatalytic front is sustained by the reaction network, which uses thiouronium salts, disulfides of β-aminothiols, and maleimide as starting components. The gradual actuation by the autocatalytic front enables movements such as gradual unrolling, screwing, and sequential closing of "fingers." This actuation also allows the transmission of chemical signals in a relay fashion and the conversion of a chemical signal to an electrical signal. Locations and times of spontaneous initiation of autocatalytic fronts can be preprogrammed in the spatial distribution of the reactants in the hydrogel. To approach the functionality of living matter, the actuators triggered by an autocatalytic front can be integrated into smart materials regulated by chemical circuits.

Reverse and forward engineering of protein pattern formation

Living systems employ protein pattern formation to regulate important life processes in space and time. Although pattern-forming protein networks have been identified in various prokaryotes and eukaryotes, their systematic experimental characterization is challenging owing to the complex environment of living cells. In turn, cell-free systems are ideally suited for this goal, as they offer defined molecular environments that can be precisely controlled and manipulated. Towards revealing the molecular basis of protein pattern formation, we outline two complementary approaches: the biochemical reverse engineering of reconstituted networks and the de novo design, or forward engineering, of artificial self-organizing systems. We first illustrate the reverse engineering approach by the example of the Escherichia coli Min system, a model system for protein self-organization based on the reversible and energy-dependent interaction of the ATPase MinD and its activating protein MinE with a lipid membrane. By reconstituting MinE mutants impaired in ATPase stimulation, we demonstrate how large-scale Min protein patterns are modulated by MinE activity and concentration. We then provide a perspective on the de novo design of self-organizing protein networks. Tightly integrated reverse and forward engineering approaches will be key to understanding and engineering the intriguing phenomenon of protein pattern formation.This article is part of the theme issue 'Self-organization in cell biology'.

Grip on complexity in chemical reaction networks

A new discipline of "systems chemistry" is emerging, which aims to capture the complexity observed in natural systems within a synthetic chemical framework. Living systems rely on complex networks of chemical reactions to control the concentration of molecules in space and time. Despite the enormous complexity in biological networks, it is possible to identify network motifs that lead to functional outputs such as bistability or oscillations. To truly understand how living systems function, we need a complete understanding of how chemical reaction networks (CRNs) create function. We propose the development of a bottom-up approach to design and construct CRNs where we can follow the influence of single chemical entities on the properties of the network as a whole. Ultimately, this approach should allow us to not only understand such complex networks but also to guide and control their behavior.

Serotyping, antibiotic susceptibility, and virulence genes screening of Escherichia coli isolates obtained from diarrheic buffalo calves in Egyptian farms

AIM

In Egypt as in many other countries, river water buffalo (Bubalus bubalis) is considered an important source of high-quality milk and meat supply. The objective of this study was to investigate serotypes, virulence genes, and antibiotic resistance determinants profiles of Escherichia coli isolated from buffalo at some places in Egypt; noticibly, this issue was not discussed in the country yet.

MATERIALS AND METHODS

A number of 58 rectal samples were collected from diarrheic buffalo calves in different regions in Egypt, and bacteriological investigated for E. coli existence. The E. coli isolates were biochemically, serologicaly identified, tested for antibiotic susceptibility, and polymerase chain reaction (PCR) analyzed for the presence of antibiotic resistance determinants and virulence genes.

RESULTS

Overall 14 isolates typed as E. coli (24.1%); 6 were belonged to serogroup O78 (10.3%), followed by O125 (4 isolates, 6.9%), then O158 (3 isolates, 5.2%) and one isolate O8 (1.7%), among them, there were 5 E. coli isolates showed a picture of hemolysis (35.7%). The isolates exhibited a high resistance to β lactams over 60%, followed by sulfa (50%) and aminoglucoside (42.8%) group, in the same time the isolates were sensitive to quinolone, trimethoprim-sulfamethoxazole, tetracycline (100%), and cephalosporine groups (71.4%). A multiplex PCR was applied to the 14 E. coli isolates revealed that all were carrying at least one gene, as 10 carried blaTEM (71.4%), 8 Sul1 (57.1%), and 6 aadB (42.8%), and 9 isolates could be considered multidrug resistant (MDR) by an incidence of 64.3%. A PCR survey was stratified for the most important E. coli virulence genes, and showed the presence of Shiga toxins in 9 isolates carried either one or the two Stx genes (64.3%), 5 isolates carried hylA gene (35.7%), and eae in 2 isolates only (14.3%), all isolates carried at least one virulence gene except two (85.7%).

CONCLUSION

The obtained data displayed that in Egypt, buffalo as well as other ruminants could be a potential source of MDR pathogenic E. coli variants which have a public health importance.

Free-standing supramolecular hydrogel objects by reaction-diffusion

Self-assembly provides access to a variety of molecular materials, yet spatial control over structure formation remains difficult to achieve. Here we show how reaction-diffusion (RD) can be coupled to a molecular self-assembly process to generate macroscopic free-standing objects with control over shape, size, and functionality. In RD, two or more reactants diffuse from different positions to give rise to spatially defined structures on reaction. We demonstrate that RD can be used to locally control formation and self-assembly of hydrazone molecular gelators from their non-assembling precursors, leading to soft, free-standing hydrogel objects with sizes ranging from several hundred micrometres up to centimeters. Different chemical functionalities and gradients can easily be integrated in the hydrogel objects by using different reactants. Our methodology, together with the vast range of organic reactions and self-assembling building blocks, provides a general approach towards the programmed fabrication of soft microscale objects with controlled functionality and shape.

Materials learning from life: concepts for active, adaptive and autonomous molecular systems

A broad overview of functional aspects in biological and synthetic out-of-equilibrium systems.

Stable DNA-based reaction–diffusion patterns

This paper demonstrates the generation of enzyme free DNA reaction–diffusion gradientsin vitrothat remain stable for tens of hours.

The nanotechnology of life-inspired systems

For some decades now, nanotechnology has been touted as the 'next big thing' with potential impact comparable to the steam, electricity or Internet revolutions - but has it lived up to these expectations? While advances in top-down nanolithography, now reaching 10-nm resolution, have resulted in devices that are rapidly approaching mass production, attempts to produce nanoscale devices using bottom-up approaches have met with only limited success. We have been inundated with nanoparticles of almost any shape, material and composition, but their societal impact has been far from revolutionary, with growing concerns over their toxicity. Despite nebulous hopes that making hierarchical nanomaterials will lead to new, emergent properties, no breakthrough applications seem imminent. In this Perspective, we argue that the time is ripe to look beyond individual nano-objects and their static assemblies, and instead focus on systems comprising different types of 'nanoparts' interacting and/or communicating with one another to perform desired functions. Such systems are interesting for a variety of reasons: they can act autonomously without external electrical or optical connections, can be dynamic and reconfigurable, and can act as 'nanomachines' by directing the flow of mass, energy or information . In thinking how this systems nanoscience approach could be implemented to design useful - as opposed to toy-model - nanosystems, our choice of applications and our nanoengineering should be inspired by living matter.

Automated design of programmable enzyme-driven DNA circuits

Molecular programming allows for the bottom-up engineering of biochemical reaction networks in a controlled in vitro setting. These engineered biochemical reaction networks yield important insight in the design principles of biological systems and can potentially enrich molecular diagnostic systems. The DNA polymerase-nickase-exonuclease (PEN) toolbox has recently been used to program oscillatory and bistable biochemical networks using a minimal number of components. Previous work has reported the automatic construction of in silico descriptions of biochemical networks derived from the PEN toolbox, paving the way for generating networks of arbitrary size and complexity in vitro. Here, we report an automated approach that further bridges the gap between an in silico description and in vitro realization. A biochemical network of arbitrary complexity can be globally screened for parameter values that display the desired function and combining this approach with robustness analysis further increases the chance of successful in vitro implementation. Moreover, we present an automated design procedure for generating optimal DNA sequences, exhibiting key characteristics deduced from the in silico analysis. Our in silico method has been tested on a previously reported network, the Oligator, and has also been applied to the design of a reaction network capable of displaying adaptation in one of its components. Finally, we experimentally characterize unproductive sequestration of the exonuclease to phosphorothioate protected ssDNA strands. The strong nonlinearities in the degradation of active components caused by this unintended cross-coupling are shown computationally to have a positive effect on adaptation quality.

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli.

Digital biology and chemistry

This account examines developments in "digital" biology and chemistry within the context of microfluidics, from a personal perspective. Using microfluidics as a frame of reference, we identify two areas of research within digital biology and chemistry that are of special interest: (i) the study of systems that switch between discrete states in response to changes in chemical concentration of signals, and (ii) the study of single biological entities such as molecules or cells. In particular, microfluidics accelerates analysis of switching systems (i.e., those that exhibit a sharp change in output over a narrow range of input) by enabling monitoring of multiple reactions in parallel over a range of concentrations of signals. Conversely, such switching systems can be used to create new kinds of microfluidic detection systems that provide "analog-to-digital" signal conversion and logic. Microfluidic compartmentalization technologies for studying and isolating single entities can be used to reconstruct and understand cellular processes, study interactions between single biological entities, and examine the intrinsic heterogeneity of populations of molecules, cells, or organisms. Furthermore, compartmentalization of single cells or molecules in "digital" microfluidic experiments can induce switching in a range of reaction systems to enable sensitive detection of cells or biomolecules, such as with digital ELISA or digital PCR. This "digitizing" offers advantages in terms of robustness, assay design, and simplicity because quantitative information can be obtained with qualitative measurements. While digital formats have been shown to improve the robustness of existing chemistries, we anticipate that in the future they will enable new chemistries to be used for quantitative measurements, and that digital biology and chemistry will continue to provide further opportunities for measuring biomolecules, understanding natural systems more deeply, and advancing molecular and cellular analysis. Microfluidics will impact digital biology and chemistry and will also benefit from them if it becomes massively distributed.

Threshold sensing through a synthetic enzymatic reaction-diffusion network

A wet stamping method to precisely control concentrations of enzymes and inhibitors in place and time inside layered gels is reported. By combining enzymatic reactions such as autocatalysis and inhibition with spatial delivery of components through soft lithographic techniques, a biochemical reaction network capable of recognizing the spatial distribution of an enzyme was constructed. The experimental method can be used to assess fundamental principles of spatiotemporal order formation in chemical reaction networks.

Fluorescent hydrogels for studying Ca2+-dependent reaction–diffusion processes

Here, we report a convenient experimental platform to study the diffusion of Ca²⁺ in the presence of a Ca²⁺-binding protein (Calbindin D28k). This work opens up new possibilities to elucidate the physical chemistry of complex Ca²⁺-dependent reaction–diffusion networks that are abundant in living cells.