Living cells and biological mechanisms as prototypes for developing chemical artificial intelligence

Artificial Intelligence (AI) is having a revolutionary impact on our societies. It is helping humans in facing the global challenges of this century. Traditionally, AI is developed in software or through neuromorphic engineering in hardware. More recently, a brand-new strategy has been proposed. It is the so-called Chemical AI (CAI), which exploits molecular, supramolecular, and systems chemistry in wetware to mimic human intelligence. In this work, two promising approaches for boosting CAI are described. One regards designing and implementing neural surrogates that can communicate through optical or chemical signals and give rise to networks for computational purposes and to develop micro/nanorobotics. The other approach concerns "bottom-up synthetic cells" that can be exploited for applications in various scenarios, including future nano-medicine. Both topics are presented at a basic level, mainly to inform the broader audience of non-specialists, and so favour the rise of interest in these frontier subjects.

Achievements and perspectives of synthetic biology in botanical insecticides

Botanical insecticides are the origin of all insecticidal compounds. They have been widely used to control pests in crops for a long time. Currently, the commercial production of botanical insecticides extracted from plants is limited because of insufficient raw material supply. Synthetic biology is a promising and effective approach for addressing the current problems of the production of botanical insecticides. It is an emerging biological research hotspot in the field of botanical insecticides. However, the biosynthetic pathways of many botanical insecticides are not completely elucidated. On the other hand, the cytotoxicity of botanical pesticides and low efficiency of these biosynthetic enzymes in new hosts make it still challenging for their heterologous production. In the present review, we summarized the recent developments in the heterologous production of botanical insecticides, analyzed the current challenges, and discussed the feasible production strategies, focusing on elucidating biosynthetic pathways, enzyme engineering, host engineering, and cytotoxicity engineering. Looking to the future, synthetic biology promises to further advance heterologous production of more botanical pesticides.

Multiplexed drug-based selection and counterselection genetic manipulations in Drosophila

The power of Drosophila melanogaster as a model system relies on tractable germline genetic manipulations. Despite Drosophila's expansive genetics toolbox, such manipulations are still accomplished one change at a time and depend predominantly on phenotypic screening. We describe a drug-based genetic platform consisting of four selection and two counterselection markers, eliminating the need to screen for modified progeny. These markers work reliably individually or in combination to produce specific genetic outcomes. We demonstrate three example applications of multiplexed drug-based genetics by generating (1) transgenic animals, expressing both components of binary overexpression systems in a single transgenesis step; (2) dual selectable and counterselectable balancer chromosomes; and (3) selectable, fluorescently tagged P[acman] bacterial artificial chromosome (BAC) strains. We perform immunoprecipitation followed by proteomic analysis on one tagged BAC line, demonstrating our platform's applicability to biological discovery. Lastly, we provide a plasmid library resource to facilitate custom transgene design and technology transfer to other model systems.

Bacterial cellulose spheroids as building blocks for 3D and patterned living materials and for regeneration

Engineered living materials (ELMs) based on bacterial cellulose (BC) offer a promising avenue for cheap-to-produce materials that can be programmed with genetically encoded functionalities. Here we explore how ELMs can be fabricated in a modular fashion from millimetre-scale biofilm spheroids grown from shaking cultures of Komagataeibacter rhaeticus. Here we define a reproducible protocol to produce BC spheroids with the high yield bacterial cellulose producer K. rhaeticus and demonstrate for the first time their potential for their use as building blocks to grow ELMs in 3D shapes. Using genetically engineered K. rhaeticus, we produce functionalized BC spheroids and use these to make and grow patterned BC-based ELMs that signal within a material and can sense and report on chemical inputs. We also investigate the use of BC spheroids as a method to regenerate damaged BC materials and as a way to fuse together smaller material sections of cellulose and synthetic materials into a larger piece. This work improves our understanding of BC spheroid formation and showcases their great potential for fabricating, patterning and repairing ELMs based on the promising biomaterial of bacterial cellulose.

Bacterial cellulose is a promising cheap-to-produce programmable engineered living material. Here the authors present a method for production of spheroids for use as engineerable building blocks able to sense and respond to chemical inputs.

RNA-Cleaving DNA Thresholder Controlled by Concentrations of miRNA Cancer Marker

Oligonucleotide gene therapy (OGT) agents suppress specific mRNAs in cells and thus reduce the expression of targeted genes. The ability to unambiguously distinguish cancer from healthy cells can solve the low selectivity problem of OGT agents. Cancer RNA markers are expressed in both healthy and cancer cells with a higher expression level in cancer cells. We have designed a DNA-based construct, named DNA thresholder (DTh) that cleaves targeted RNA only at high concentrations of cancer marker RNA and demonstrates low cleavage activity at low marker concentrations. The RNA-cleaving activity can be adjusted within one order of magnitude of the cancer marker RNA concentration by simply redesigning DTh. Importantly, DTh recognizes cancer marker RNA, while cleaving targeted RNA; this offers a possibility to suppress vital genes exclusively in cancer cells, thus triggering their death. DTh is a prototype of computation-inspired molecular device for controlling gene expression and cancer treatment.

Tunable Gene Expression System Independent of Downstream Coding Sequence

Fine control of the expression levels of proteins constitutes a major challenge in synthetic biology and metabolic engineering. However, the dependence of translation initiation on the downstream coding sequence (CDS) obscures accurate prediction of the protein expression levels from mRNA sequences. Here, we present a tunable gene-expression system comprising 24 expression cassettes that produce predefined relative expression levels of proteins ranging from 0.001 to 1 without being influenced by the downstream CDS. To validate the practical utility of the tunable expression system, it was applied to a synthetic circuit displaying three states of fluorescence depending on the difference in protein expression levels. To demonstrate the suitability of application to metabolic engineering, this system was used to diversify the levels of key metabolic enzymes. As a result, expression-optimized strains were capable of producing 2.25 g/L of cadaverine, 2.59 g/L of L-proline, and 95.7 mg/L of 1-propanol. Collectively, the tunable expression system could be utilized to optimize genetic circuits for desired operation and to optimize metabolic fluxes through biosynthetic pathways for enhancing production yields of bioproducts. This tunable system will be useful for studying basic and applied biological sciences in addition to applications in synthetic biology and metabolic engineering.

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

Design and evaluation of biological gate circuits and their therapeutic applications in a model of multidrug resistant cancers

OBJECTIVES

Synthetic biology is primarily an emerging research field that consists of designing new synthetic gene circuits dedicated to targeted functions and therapies such as cancer therapy. In this study, a genetic logic NOT-IF gate is used to reduce the multidrug resistance and facilitate the malignant cancer therapy. MCF7 cancer cells were cultured in RPMI-1640 medium and transfected with lentiviral vectors including MDR1 gene and the corresponding shRNA against MDR1 with controllable promoters. Transcript levels and protein levels of MDR1 gene were quantified.

RESULTS

Our results showed that when doxycycline (DOX) and sodium butyrate were present and IPTG was absent, these led to a 74,354-fold increase in MDR1 gene expression. Upon IPTG treatment, the MDR1 gene expression was not detected due to the lack of the inducer. In addition, following IPTG induction in the presence of DOX and sodium butyrate and expressing shRNA, there was a 75% reduction in MDR1 gene expression compared to those cells treated only with sodium butyrate and DOX.

CONCLUSIONS

We successfully designed and implemented the genetic logic NOT-IF gate at the transcriptional level using the inducible expression of both MDR1 drug resistance pump and its specific shRNA in MCF7 cancer cells, using the third generation lentiviral vectors.

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 a 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/dicyclopropyl ketone) and shown to perform effectively in both Escherichia 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.

High-Performance Biocomputing in Synthetic Biology-Integrated Transcriptional and Metabolic Circuits

Biocomputing uses molecular biology parts as the hardware to implement computational devices. By following pre-defined rules, often hard-coded into biological systems, these devices are able to process inputs and return outputs—thus computing information. Key to the success of any biocomputing endeavor is the availability of a wealth of molecular tools and biological motifs from which functional devices can be assembled. Synthetic biology is a fabulous playground for such purpose, offering numerous genetic parts that allow for the rational engineering of genetic circuits that mimic the behavior of electronic functions, such as logic gates. A grand challenge, as far as biocomputing is concerned, is to expand the molecular hardware available beyond the realm of genetic parts by tapping into the host metabolism. This objective requires the formalization of the interplay of genetic constructs with the rest of the cellular machinery. Furthermore, the field of metabolic engineering has had little intersection with biocomputing thus far, which has led to a lack of definition of metabolic dynamics as computing basics. In this perspective article, we advocate the conceptualization of metabolism and its motifs as the way forward to achieve whole-cell biocomputations. The design of merged transcriptional and metabolic circuits will not only increase the amount and type of information being processed by a synthetic construct, but will also provide fundamental control mechanisms for increased reliability.

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 embedding of 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 gene circuits for the detection, elimination and prevention of disease

In living organisms, naturally evolved sensors that constantly monitor and process environmental cues trigger corrective actions that enable the organisms to cope with changing conditions. Such natural processes have inspired biologists to construct synthetic living sensors and signalling pathways, by repurposing naturally occurring proteins and by designing molecular building blocks de novo, for customized diagnostics and therapeutics. In particular, designer cells that employ user-defined synthetic gene circuits to survey disease biomarkers and to autonomously re-adjust unbalanced pathological states can coordinate the production of therapeutics, with controlled timing and dosage. Furthermore, tailored genetic networks operating in bacterial or human cells have led to cancer remission in experimental animal models, owing to the network's unprecedented specificity. Other applications of designer cells in infectious, metabolic and autoimmune diseases are also being explored. In this Review, we describe the biomedical applications of synthetic gene circuits in major disease areas, and discuss how the first genetically engineered devices developed on the basis of synthetic-biology principles made the leap from the laboratory to the clinic.

Serine Integrases: Advancing Synthetic Biology

Serine integrases catalyze precise rearrangement of DNA through site-specific recombination of small sequences of DNA called attachment (att) sites. Unlike other site-specific recombinases, the recombination reaction driven by serine integrases is highly directional and can only be reversed in the presence of an accessory protein called a recombination directionality factor (RDF). The ability to control reaction directionality has led to the development of serine integrases as tools for controlled rearrangement and modification of DNA in synthetic biology, gene therapy, and biotechnology. This review discusses recent advances in serine integrase technologies focusing on their applications in genome engineering, DNA assembly, and logic and data storage devices.

Cellular Biosensors with Engineered Genetic Circuits

An increasing interest in building novel biological devices with designed cellular functionalities has triggered the search of innovative tools for biocomputation. Utilizing the tools of synthetic biology, numerous genetic circuits have been implemented such as engineered logic operation in analog and digital circuits. Whole cell biosensors are widely used biological devices that employ several biocomputation tools to program cells for desired functions. Up to the present date, a wide range of whole-cell biosensors have been designed and implemented for disease theranostics, biomedical applications, and environmental monitoring. In this review, we investigated the recent developments in biocomputation tools such as analog, digital, and mix circuits, logic gates, switches, and state machines. Additionally, we stated the novel applications of biological devices with computing functionalities for diagnosis and therapy of various diseases such as infections, cancer, or metabolic diseases, as well as the detection of environmental pollutants such as heavy metals or organic toxic compounds. Current whole-cell biosensors are innovative alternatives to classical biosensors; however, there is still a need to advance decision making capabilities by developing novel biocomputing devices.