Immunomimetic Designer Cells Protect Mice from MRSA Infection.

Many community- and hospital-acquired bacterial infections are caused by antibiotic-resistant pathogens. Methicillin-resistant Staphylococcus aureus (MRSA) predisposes humans to invasive infections that are difficult to eradicate. We designed a closed-loop gene network programming mammalian cells to autonomously detect and eliminate bacterial infections. The genetic circuit contains human Toll-like receptors as the bacterial sensor and a synthetic promoter driving reversible and adjustable expression of lysostaphin, a bacteriolytic enzyme highly lethal to S. aureus. Immunomimetic designer cells harboring this genetic circuit exhibited fast and robust sense-and-destroy kinetics against live staphylococci. When tested in a foreign-body infection model in mice, microencapsulated cell implants prevented planktonic MRSA infection and reduced MRSA biofilm formation by 91%. Notably, this system achieved a 100% cure rate of acute MRSA infections, whereas conventional vancomycin treatment failed. These results suggest that immunomimetic designer cells could offer a therapeutic approach for early detection, prevention, and cure of pathogenic infections in the post-antibiotic era.

Single-Nucleotide-Resolution Computing and Memory in Living Cells.

The ability to process and store information in living cells is essential for developing next-generation therapeutics and studying biology in situ. However, existing strategies have limited recording capacity and are challenging to scale. To overcome these limitations, we developed DOMINO, a robust and scalable platform for encoding logic and memory in bacterial and eukaryotic cells. Using an efficient single-nucleotide-resolution Read-Write head for DNA manipulation, DOMINO converts the living cells' DNA into an addressable, readable, and writable medium for computation and storage. DOMINO operators enable analog and digital molecular recording for long-term monitoring of signaling dynamics and cellular events. Furthermore, multiple operators can be layered and interconnected to encode order-independent, sequential, and temporal logic, allowing recording and control over the combination, order, and timing of molecular events in cells. We envision that DOMINO will lay the foundation for building robust and sophisticated computation-and-memory gene circuits for numerous biotechnological and biomedical applications.

A synthetic, closed-looped gene circuit for the autonomous regulation of RUNX2 activity during chondrogenesis.

The transcription factor RUNX2 is a key regulator of chondrocyte phenotype during development, making it an ideal target for prevention of undesirable chondrocyte maturation in cartilage tissue-engineering strategies. Here, we engineered an autoregulatory gene circuit (cisCXp-shRunx2) that negatively controls RUNX2 activity in chondrogenic cells via RNA interference initiated by a tunable synthetic Col10a1-like promoter (cisCXp). The cisCXp-shRunx2 gene circuit is designed based on the observation that induced RUNX2 silencing after early chondrogenesis enhances the accumulation of cartilaginous matrix in ATDC5 cells. We show that the cisCXp-shRunx2 initiates RNAi of RUNX2 in maturing chondrocytes in response to the increasing intracellular RUNX2 activity without interfering with early chondrogenesis. The induced loss of RUNX2 activity in turn negatively regulates the gene circuit itself. Moreover, the efficacy of RUNX2 suppression from cisCXp-shRunx2 can be controlled by modifying the sensitivity of cisCXp promoter. Finally, we show the efficacy of inhibiting RUNX2 in preventing matrix loss in human mesenchymal stem cell-derived (hMSC-derived) cartilage under conditions that induce chondrocyte hypertrophic differentiation, including inflammation. Overall, our results demonstrated that the negative modulation of RUNX2 activity with our autoregulatory gene circuit enhanced matrix synthesis and resisted ECM degradation by reprogrammed MSC-derived chondrocytes in response to the microenvironment of the degenerative joint.

A genetic mammalian proportional-integral feedback control circuit for robust and precise gene regulation.

The processes that keep a cell alive are constantly challenged by unpredictable changes in its environment. Cells manage to counteract these changes by employing sophisticated regulatory strategies that maintain a steady internal milieu. Recently, the antithetic integral feedback motif has been demonstrated to be a minimal and universal biological regulatory strategy that can guarantee robust perfect adaptation for noisy gene regulatory networks in Escherichia coli. Here, we present a realization of the antithetic integral feedback motif in a synthetic gene circuit in mammalian cells. We show that the motif robustly maintains the expression of a synthetic transcription factor at tunable levels even when it is perturbed by increased degradation or its interaction network structure is perturbed by a negative feedback loop with an RNA-binding protein. We further demonstrate an improved regulatory strategy by augmenting the antithetic integral motif with additional negative feedback to realize antithetic proportional-integral control. We show that this motif produces robust perfect adaptation while also reducing the variance of the regulated synthetic transcription factor. We demonstrate that the integral and proportional-integral feedback motifs can mitigate the impact of gene expression burden, and we computationally explore their use in cell therapy. We believe that the engineering of precise and robust perfect adaptation will enable substantial advances in industrial biotechnology and cell-based therapeutics.

Spatial biology of Ising-like synthetic genetic networks.

BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells.

During development, cell state transitions are coordinated through changes in the identity of molecular regulators in a cell type- and dose-specific manner. The ability to rationally engineer such transitions in human pluripotent stem cells (hPSC) will enable numerous applications in regenerative medicine. Herein, we report the generation of synthetic gene circuits that can detect a desired cell state using AND-like logic integration of endogenous miRNAs (classifiers) and, upon detection, produce fine-tuned levels of output proteins using an miRNA-mediated output fine-tuning technology (miSFITs). Specifically, we created an "hPSC ON" circuit using a model-guided miRNA selection and circuit optimization approach. The circuit demonstrates robust PSC-specific detection and graded output protein production. Next, we used an empirical approach to create an "hPSC-Off" circuit. This circuit was applied to regulate the secretion of endogenous BMP4 in a state-specific and fine-tuned manner to control the composition of differentiating hPSCs. Our work provides a platform for customized cell state-specific control of desired physiological factors in hPSC, laying the foundation for programming cell compositions in hPSC-derived tissues and beyond.

The design of synthetic gene circuits in plants: new components, old challenges.

The fascination produced by the possibility of engineering plants with augmented capabilities has accompanied plant biotechnology since its origins. This prospect has become even more relevant in present times under the pressure imposed by climate change and population growth. Today's plant biotechnologists approach this challenge with the tools of synthetic biology, which facilitate the assembly of synthetic gene circuits (SGCs) from their modular components. Transcriptional SGCs take environmental or endogenous inputs and operate them using transcriptional signals in ways that do not necessarily occur in nature, generating new physiological outputs. Many genetic components have been developed over the years that can be employed in the design and construction of plant SGCs. This review aims to provide an updated view of the components available, proposing a general scheme that facilitates the classification of circuit components in sensor, processor, and actuator modules. Following this analogy, we review the latest advances in the design of SGCs and discuss the main challenges ahead.

A single promoter-TALE system for tissue-specific and tuneable expression of multiple genes in rice.

In biological discovery and engineering research, there is a need to spatially and/or temporally regulate transgene expression. However, the limited availability of promoter sequences that are uniquely active in specific tissue-types and/or at specific times often precludes co-expression of multiple transgenes in precisely controlled developmental contexts. Here, we developed a system for use in rice that comprises synthetic designer transcription activator-like effectors (dTALEs) and cognate synthetic TALE-activated promoters (STAPs). The system allows multiple transgenes to be expressed from different STAPs, with the spatial and temporal context determined by a single promoter that drives expression of the dTALE. We show that two different systems-dTALE1-STAP1 and dTALE2-STAP2-can activate STAP-driven reporter gene expression in stable transgenic rice lines, with transgene transcript levels dependent on both dTALE and STAP sequence identities. The relative strength of individual STAP sequences is consistent between dTALE1 and dTALE2 systems but differs between cell-types, requiring empirical evaluation in each case. dTALE expression leads to off-target activation of endogenous genes but the number of genes affected is substantially less than the number impacted by the somaclonal variation that occurs during the regeneration of transformed plants. With the potential to design fully orthogonal dTALEs for any genome of interest, the dTALE-STAP system thus provides a powerful approach to fine-tune the expression of multiple transgenes, and to simultaneously introduce different synthetic circuits into distinct developmental contexts.

Development and evaluation of a qPCR detection method for citrinin in Liupao tea.

Penicillium is universal in dark tea, and Penicillium citrinum can produce a kidney toxin called citrinin (CIT). Determining CIT is difficult because of the complexity of the dark tea substrate and the diversity of CIT-producing fungi. Therefore, this study established a real-time PCR (qPCR) detection method for CIT-related synthetic genes (ctnD, orf1, ctnA, pksCT, orf5, orf7, and ctnG) in Liupao tea and determined the content of CIT in samples at different production stages and the toxin-producing abilities of fungi (Aspergillus oryzae, etc.) in Liupao tea. CIT was found in all samples during the pile-fermentation process of Liupao tea, and CIT was detected in two samples during the aging process. The established method demonstrated good sensitivity and specificity in detecting CIT-related synthetic genes. The reaction efficiency was within the preferred range of 100 ± 10%. CIT was not detected or was below the detection limit when the Ct value of one or more related synthetic genes was greater than 33.5. Therefore, the established qPCR method can effectively predict the production of CIT in Liupao tea, and it is applicable to the judgment of whether fungi produce CIT.

Bacillus integrative plasmid system combining a synthetic gene circuit for efficient genetic modifications of undomesticated Bacillus strains.

BACKGROUND: Owing to CRISPR-Cas9 and derivative technologies, genetic studies on microorganisms have dramatically increased. However, the CRISPR-Cas9 system is still difficult to utilize in many wild-type Bacillus strains owing to Cas9 toxicity. Moreover, less toxic systems, such as cytosine base editors, generate unwanted off-target mutations that can interfere with the genetic studies of wild-type strains. Therefore, a convenient alternative system is required for genetic studies and genome engineering of wild-type Bacillus strains. Because wild-type Bacillus strains have poor transformation efficiencies, the new system should be based on broad-host-range plasmid-delivery systems. RESULTS: Here, we developed a Bacillus integrative plasmid system in which plasmids without the replication initiator protein gene (rep) of Bacillus are replicated in a donor Bacillus strain by Rep proteins provided in trans but not in Bacillus recipients. The plasmids were transferred to recipients through a modified integrative and conjugative element, which is a wide host range plasmid-delivery system. Genetic mutations were generated in recipients through homologous recombination between the transferred plasmid and the genome. The system was improved by adding a synthetic gene circuit for efficient screening of the desired mutations by double crossover recombination in recipient strains. The improved system exhibited a mutation efficiency of the target gene of approximately 100% in the tested wild-type Bacillus strains. CONCLUSION: The Bacillus integrative plasmid system developed in this study can generate target mutations with high efficiency when combined with a synthetic gene circuit in wild-type Bacillus strains. The system is free of toxicity and unwanted off-target mutations as it generates the desired mutations by traditional double crossover recombination. Therefore, our system could be a powerful tool for genetic studies and genome editing of Cas9-sensitive wild-type Bacillus strains.

Engineering Closed-Loop, Autoregulatory Gene Circuits for Osteoarthritis Cell-Based Therapies.

PURPOSE OF REVIEW: Genetic engineering offers the possibility to simultaneously target multiple cellular pathways in the joints affected by osteoarthritis (OA). The purpose of this review is to summarize the ongoing efforts to develop disease-modifying osteoarthritis drugs (DMOADs) using genetic engineering, including targeting approaches, genome editing techniques, and delivery methods. RECENT FINDINGS: Several gene circuits have been developed that reprogram cells to autonomously target inflammation, and their efficacy has been demonstrated in chondrocytes and stem cells. Gene circuits developed for metabolic disorders, such as those targeting insulin resistance and obesity, also have the potential to mitigate the impact of these conditions on OA onset and/or progression. Despite the strides made in characterizing the inflammatory environment of the OA joint, our incomplete understanding of how the multiple regulators interact to control signal transduction, gene transcription, and translation to protein limits the development of targeted disease-modifying therapeutics. Continuous advances in targeted genome editing, combined with online toolkits that simplify the design and production of gene circuits, have the potential to accelerate the discovery and clinical application of multi-target gene circuits with disease-modifying properties for the treatment of OA.

5'-DMT-protected double-stranded DNA: Synthesis and competence to enzymatic reactions.

The functionalization of 5'-OH group in nucleic acids is of significant value for molecular biology. In the current work we discovered that acid-labile 4,4'-dimethoxytrityl protecting group (DMT) of oligonucleotides (ONs) is stable under PCR conditions and does not interfere with activity of DNA polymerases. So application of 5'-DMT-protected ONs could allow producing both symmetric and asymmetric 5'-DMT-blocked double-stranded DNA (dsDNA) fragments. We demonstrated that the presence of thiol compounds (mercaptoethanol and dithiothreitol) in PCR mixture is undesirable for the stability of DMT-group. DMT-ONs can be successfully used during polymerase chain assembly of synthetic genes. We tested 5'-DMT dsDNA in blunt-end DNA ligation reaction by T4 DNA ligase and found that it could not be ligated with 5'-phosphorylated DNA fragments, namely linearized plasmid vector pJET1.2/blunt. Possible reason for this is steric hindrance created by bulky and rigid DMT-group, that prevents entering enzyme active site. We also demonstrated that 5'-DMT modification of dsDNA does not affect activity of T5 5',3'-exonuclease towards both ssDNA and dsDNA. Further screening of the exonucleases, sensitive to 5'-DMT-modification or search of ways to separate long 5'-DMT-ssDNA and 5'-OH-ssDNA could allow finding application of 5'-DMT-modified oligo- and polynucleotides.

Codon pair optimization (CPO): a software tool for synthetic gene design based on codon pair bias to improve the expression of recombinant proteins in Pichia pastoris.

BACKGROUND: Codon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias. RESULTS: In this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris. CONCLUSIONS: Codon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

Multiscale effects of heating and cooling on genes and gene networks.

Most organisms must cope with temperature changes. This involves genes and gene networks both as subjects and agents of cellular protection, creating difficulties in understanding. Here, we study how heating and cooling affect expression of single genes and synthetic gene circuits in Saccharomyces cerevisiae We discovered that nonoptimal temperatures induce a cell fate choice between stress resistance and growth arrest. This creates dramatic gene expression bimodality in isogenic cell populations, as arrest abolishes gene expression. Multiscale models incorporating population dynamics, temperature-dependent growth rates, and Arrhenius scaling of reaction rates captured the effects of cooling, but not those of heating in resistant cells. Molecular-dynamics simulations revealed how heating alters the conformational dynamics of the TetR repressor, fully explaining the experimental observations. Overall, nonoptimal temperatures induce a cell fate decision and corrupt gene and gene network function in computationally predictable ways, which may aid future applications of engineered microbes in nonstandard temperatures.

Ustiloxin biosynthetic machinery is not compatible between Aspergillus flavus and Ustilaginoidea virens.

Ustiloxins are ribosomally synthesized and post-translationally modified peptides (RiPPs) first reported in Ascomycetes. Originally identified as metabolites of the rice pathogenic fungus Ustilaginoidea virens, they were recently identified among the metabolites of the mold Aspergillus flavus, along with their corresponding biosynthetic gene cluster. Ustilaginoidea virens produces ustiloxins A and B, whereas A. flavus produces only ustiloxin B. Correspondingly, in U. virens, the ustiloxin precursor peptide, from which the compound backbone is cleaved and cyclized, contains the core peptides Tyr(Y)-Val(V)-Ile(I)-Gly(G) and Tyr(Y)-Ala(A)-Ile(I)-Gly(G) for ustiloxins A and B, respectively, whereas that of A. flavus contains only the YAIG motif for ustiloxin B. In this study, the gene that encodes the precursor peptide in A. flavus, ustA, was replaced with synthetic genes encoding the core peptides YVIG or FAIG, to investigate their compatibility with the ustiloxin biosynthetic machinery. We also examined the importance of the hydroxyl group on the aromatic ring of Tyr for cyclization of the YAIG core peptide. Against our expectation, the ustA variant possessing YVIG core peptides did not produce a detectable amount of ustiloxin A, even though the ustiloxin biosynthetic gene clusters of A. flavus and U. virens both contain 13 homologous genes. We confirmed that the lack of ustiloxin A production was not due to lack or insufficient expression of the substituted synthetic gene. This result, along with the differences between the primary sequences of UstYa and UstYb in A. flavus and U. virens, suggests that the ustiloxin biosynthetic machinery is optimized for the native core peptide sequences. The synthetic FAIG-encoding ustA did not yield any compounds specific to the FAIG core peptide, suggesting that the hydroxyl group on the aromatic ring of Tyr in the core peptide is indispensable for cyclization of the core peptide, even though it is not structurally involved in the cyclization.

Reinforcement learning in synthetic gene circuits.

Synthetic gene circuits allow programming in DNA the expression of a phenotype at a given environmental condition. The recent integration of memory systems with gene circuits opens the door to their adaptation to new conditions and their re-programming. This lays the foundation to emulate neuromorphic behaviour and solve complex problems similarly to artificial neural networks. Cellular products such as DNA or proteins can be used to store memory in both digital and analog formats, allowing cells to be turned into living computing devices able to record information regarding their previous states. In particular, synthetic gene circuits with memory can be engineered into living systems to allow their adaptation through reinforcement learning. The development of gene circuits able to adapt through reinforcement learning moves Sciences towards the ambitious goal: the bottom-up creation of a fully fledged living artificial intelligence.

Processing two environmental chemical signals with a synthetic genetic IMPLY gate, a 2-input-2-output integrated logic circuit, and a process pipeline to optimize its systems chemistry in Escherichia coli.

Synthetic genetic devices can perform molecular computation in living bacteria, which may sense more than one environmental chemical signal, perform complex signal processing in a human-designed way, and respond in a logical manner. IMPLY is one of the four fundamental logic functions and unlike others, it is an "IF-THEN" constraint-based logic. By adopting physical hierarchy of electronics in the realm of in-cell systems chemistry, a full-spectrum transcriptional cascaded synthetic genetic IMPLY gate, which senses and integrates two environmental chemical signals, is designed, fabricated, and optimized in a single Escherichia coli cell. This IMPLY gate is successfully integrated into a 2-input-2-output integrated logic circuit and showed higher signal-decoding efficiency. Further, we showed simple application of those devices by integrating them with an inherent cellular process, where we controlled the cell morphology and color in a logical manner. To fabricate and optimize the genetic devices, a new process pipeline named NETWORK Brick is developed. This pipeline allows fast parallel kinetic optimization and reduction in the unwanted kinetic influence of one DNA module over another. A mathematical model is developed and it shows that response of the genetic devices are digital-like and are mathematically predictable. This single-cell IMPLY gate provides the fundamental constraint-based logic and completes the in-cell molecular logic processing toolbox. The work has significance in the smart biosensor, artificial in-cell molecular computation, synthetic biology, and microbiorobotics.

Synthetic gene as target to assess the sensitivity of PCR to detect Trichinella spp. larvae in meat from a non-endemic region.

Trichinellosis is a zoonotic disease exotic in Brazil but commonly found worldwide including South American countries like Argentina. International trading of swine meat needs an official Trichinella-free diagnosis commonly carried out by pepsin-HCl digestion of diaphragm tissue fragments followed by microscopic examination for the presence or absence of Trichinella larvae. The easiness of this diagnostic method allows it to be performed at slaughtering plants but, in contrast, it lacks sensitivity and does not allow species differentiation, which is fundamental for determining geographical and species distribution of different genotypes. In our study, we aimed to evaluate a highly sensitive diagnostic method based on the polymerase chain reaction (PCR) that would allow us to detect and classify different species of Trichinella. Thus, we designed a synthetic gene and selected five sets of primers targeting specific regions of the Trichinella genome. The synthetic gene was cloned into a plasmid and then used to optimize PCR conditions. Using our PCR, we were able to detect 0.001 pg of the synthetic gene, which corresponded to 0.01 larvae. Then, we collected 175 samples of Suidae (domestic and wild boars) diaphragm fragments that were pooled into groups, digested with pepsin-HCl, and had the DNA extracted for analysis by PCR. The clinical samples evaluated were negative by PCR. Our results indicate that the PCR-based method might be a useful diagnostic method complementary to the pepsin-HCl digestion method currently in use, mostly in non-endemic areas.

Expression of B subunit of E. coli heat-labile enterotoxin in the progenies of transgenic tobacco bred by crossing nuclear- and chloroplast-transgenic lines.

The B subunit of Escherichia coli heat-labile toxin (LTB) is a model antigen that induces a strong immune response upon oral administration and enhances immune responses to conjugated and co-administered antigens. We previously examined high expression levels of LTB in plants by chloroplast and synthetic LTB gene expression and found substantially higher expression levels of LTB, compared to nuclear LTB expression in wild-type plants. The 2.5% LTB protein of total soluble protein that was observed by chloroplast transformation was approximately 250-fold greater expression than that of LTB via nuclear genome integration. In addition, the amount of LTB protein found in transgenic tobacco leaves using a synthetic LTB gene was 2.2% of the total soluble plant protein, which was approximately 200-fold higher than that in plants with native LTB gene expression. The purpose of our experiment was to increase LTB levels in plants by crossing chloroplast-transformed and synthetic LTB transgenic lines produced previously to express higher LTB levels. LTB protein levels in the F1 transgenic tobacco plants was significantly higher (3.3%), compared to the 2.2% of chloroplast-transformed line or 2.8% of synthetic LTB gene line. Our results suggest that LTB expression was successfully enhanced in the F1 hybrid generation of transgenic tobacco plants.

Spatial-Stochastic modelling of synthetic gene regulatory networks.

Transcription factors are important molecules which control the levels of mRNA and proteins within cells by modulating the process of transcription (the mechanism by which mRNA is produced within cells) and hence translation (the mechanism by which proteins are produced within cells). Transcription factors are part of a wider family of molecular interaction networks known as gene regulatory networks (GRNs) which play an important role in key cellular processes such as cell division and apoptosis (e.g. the p53-Mdm2, NFκB pathways). Transcription factors exert control over molecular levels through feedback mechanisms, with proteins binding to gene sites in the nucleus and either up-regulating or down-regulating production of mRNA. In many GRNs, there is a negative feedback in the network and the transcription rate is reduced. Typically, this leads to the mRNA and protein levels oscillating over time and also spatially between the nucleus and cytoplasm. When experimental data for such systems is analysed, it is observed to be noisy and in many cases the actual numbers of molecules involved are quite low. In order to model such systems accurately and connect with the data in a quantitative way, it is therefore necessary to adopt a stochastic approach as well as take into account the spatial aspect of the problem. In this paper, we extend previous work in the area by formulating and analysing stochastic spatio-temporal models of synthetic GRNs e.g. repressilators and activator-repressor systems.