82 results found
Au HKE, Isalan M, Mielcarek M, 2021, Gene therapy advances: a meta-analysis of AAV usage in clinical settings, Frontiers in Medicine, ISSN: 2296-858X
Adeno-associated viruses (AAVs) are the safest and most effective gene delivery vehicles to drive long-term transgene expression in gene therapy. While animal studies have shown promising results, the translatability of AAVs into clinical settings has been partly limited due to their restricted gene packaging capacities, off-target transduction, and immunogenicity. In this study, we analysed over two decades of AAV applications, in 136 clinical trials. This meta-analysis aims to provide an up-to-date overview of the use and successes of AAVs in clinical trials, while evaluating the approaches used to address the above challenges. First, this study reveals that the speed of novel AAV development has varied between therapeutic areas, with particular room for improvement in Central Nervous System disorders, where development has been slow. Second, the lack of dose-dependent toxicity and efficacy data indicates that optimal dosing regimes remain elusive. Third, more clinical data on the effectiveness of various immune-modulation strategies and gene editing approaches are required to direct future research and to accelerate the translation of AAV-mediated gene therapy into human applications.
Oliver-Huidobro M, Tica J, Wachter G, et al., 2021, Synthetic spatial patterning in bacteria: advances based on novel diffusible signals, Microbial Biotechnology, ISSN: 1751-7907
Engineering multicellular patterning may help in the understanding of some fundamental laws of pattern formation and thus may contribute to the field of developmental biology. Furthermore, advanced spatial control over gene expression may revolutionize fields such as medicine, through organoid or tissue engineering. To date, foundational advances in spatial synthetic biology have often been made in prokaryotes, using artificial gene circuits. In this review, engineered patterns are classified into four levels of increasing complexity, ranging from spatial systems with no diffusible signals to systems with complex multi-diffusor interactions. This classification highlights how the field was held back by a lack of diffusible components. Consequently, we provide a summary of both previously characterized and some new potential candidate small-molecule signals that can regulate gene expression in Escherichia coli. These diffusive signals will help synthetic biologists to successfully engineer increasingly intricate, robust and tuneable spatial structures.
Mielcarek M, Isalan M, 2021, Kinetin stimulates differentiation of C2C12 myoblasts., PLoS One, Vol: 16, Pages: 1-16, ISSN: 1932-6203
Kinetin or N6-furfuryladenine (K) belongs to a class of plant hormones called cytokinins, which are biologically active molecules modulating many aspects of plant growth and development. However, biological activities of cytokinins are not only limited to plants; their effects on animals have been widely reported in the literature. Here, we found that Kinetin is a potent small molecule that efficiently stimulates differentiation of C2C12 myoblasts into myotubes in vitro. The highest efficacy was achieved at 1μM and 10μM Kinetin concentrations, in both mitogen-poor and rich media. More importantly, Kinetin was able to strongly stimulate the MyoD-dependent conversion of fibroblasts into myotubes. Kinetin alone did not give rise to fibroblast conversion and required MyoD; this demonstrates that Kinetin augments the molecular repertoire of necessary key regulatory factors to facilitate MyoD-mediated myogenic differentiation. This novel Kinetin pro-myogenic function may be explained by its ability to alter intracellular calcium levels and by its potential to impact on Reactive Oxygen Species (ROS) signalling. Taken together, our findings unravel the effects of a new class of small molecules with potent pro-myogenic activities. This opens up new therapeutic avenues with potential for treating skeletal muscle diseases related to muscle aging and wasting.
Baddeley H, Isalan M, 2021, The application of CRISPR/Cas systems for antiviral therapy, Frontiers in Genome Editing, Vol: 3, ISSN: 2673-3439
As CRISPR/Cas systems have been refined over time, there has been an effort to apply them to real world problems, such as developing sequence-targeted antiviral therapies. Viruses pose a major threat to humans and new tools are urgently needed to combat these rapidly mutating pathogens. Importantly, a variety of CRISPR systems have the potential to directly cleave DNA and RNA viral genomes, in a targeted and easily-adaptable manner, thus preventing or treating infections. This perspective article highlights recent studies using different Cas effectors against various RNA viruses causing acute infections in humans; a latent virus (HIV-1); a chronic virus (hepatitis B); and viruses infecting livestock and animal species of industrial importance. The outlook and remaining challenges are discussed, particularly in the context of tacking newly emerging viruses, such as SARS-CoV-2.
Isalan M, 2021, DNA recognition/processing: Zinc fingers: Structure and design, Encyclopedia of Biological Chemistry: Third Edition, Pages: 506-516, ISBN: 9780128194607
Prakash S, Racovita A, Varela C, et al., 2021, Engineering adaptive gene circuits in bacteria mastering game playing by reinforcement learning, The 1st International BioDesign Research Conference, Publisher: Biophysical Society, Pages: 262A-262A, ISSN: 0006-3495
Learning to solve problems is central to artificial and living intelligent systems. Although physical and chemical systems mimicking neural connectivity have been shown to solve complex problems, no living system with a synthetic genetic construction has ever been reported to learn complex algorithms such as playing board games — a classic benchmark for artificial intelligence. Engineering a synthetic genetic system in living cells able to learn and play even the simplest board games, such as tic-tac-toe, has remained elusive because it requires not only a set of gene circuits implementing the needed decision algorithms but also an adaptive memory system that can predictably adjust their strength through learning. We will report that engineered Escherichia coli encoding a library of new genetic switches — we call memregulons — that act as both memory systems and logic gates, can learn to produce predictable gene regulation. As the memregulon devices allow the design of gene circuits with predictable behaviour, we use them to implement in living cells a computational algorithm allowing the bacteria to master playing tic-tac-toe by using reinforcement learning. Learning is achieved by persistently modifying the relative expression of memregulons by applying external chemicals after each training game is won or lost, leading to new decisions. Bacteria learn by playing against other players or other bacteria in an unsupervised manner and the same library allows them to learn other types of games or algorithms.
Mielcarek M, Isalan M, 2021, Polyglutamine diseases: looking beyond the neurodegenerative universe, Neural Regeneration Research, Vol: 16, Pages: 1186-1187, ISSN: 1673-5374
Greenig M, Melville A, Huntley D, et al., 2020, Cross-sectional transcriptional analysis of the ageing murine heart, Frontiers in Molecular Biosciences, Vol: 7, Pages: 1-14, ISSN: 2296-889X
Cardiovascular disease accounts for millions of deaths each year and is currently the leading cause of mortality worldwide. The ageing process is clearly linked to cardiovascular disease, however, the exact relationship between ageing and heart function is not fully understood. Furthermore, a holistic view of cardiac ageing, linking features of early life development to changes observed in old age, has not been synthesized. Here, we re-purpose RNA-sequencing data previously-collected by our group, investigating gene expression differences between wild-type mice of different age groups that represent key developmental milestones in the murine lifespan. DESeq2’s generalized linear model was applied with two hypothesis6testing approaches to identify differentially-expressed (DE) genes, both between pairs of age groups and across mice of all ages. Pairwise comparisons identified genes associated with specific age transitions, while comparisons across all age groups identified a large set of genes associated with the ageing process more broadly. An unsupervised machine learning approach was then applied to extract common expression patterns from this set of age-associated genes. Sets of genes with both linear and non-linear expression trajectories were identified, suggesting that ageing not only involves the activation of gene expression programs unique to different age groups, but also the re-activation of gene expression programs from earlier ages. Overall, we present a comprehensive transcriptomic analysis of cardiac gene expression patterns across the entirety of the murine lifespan.
Broedel A, Rodrigues R, Jaramillo A, et al., 2020, Accelerated evolution of a minimal 63-amino acid dual transcription factor, Science Advances, Vol: 6, Pages: 1-9, ISSN: 2375-2548
Transcription factors control gene expression in all life. This raises the question of what is the smallest protein that can support such activity. In nature, Cro from bacteriophage λ is one of the smallest known repressors (66 amino acids; a.a.) and activators are typically much larger (e.g. λ cI, 237 a.a.). Indeed, previous efforts to engineer a minimal activator from λ Cro resulted in no activity in vivo, in cells. In this study, we show that directed evolution results in a new Cro activator-repressor that functions as efficiently as λ cI, in vivo. To achieve this, we develop Phagemid-Assisted Continuous Evolution: PACEmid. We find that a peptide as small as 63 a.a. functions efficiently as an activator and/or repressor. To our knowledge, this is the smallest protein activator that enables polymerase recruitment, highlighting the capacity of transcription factors to evolve from very short peptide sequences.
Tica J, Zhu T, Isalan M, 2020, Dynamical model fitting to a synthetic positive feedback circuit in E. coli, Engineering Biology, Vol: 4, Pages: 25-31, ISSN: 2398-6182
Applying the principles of engineering to Synthetic Biology relies on the development of robust and modular genetic components, as well as underlying quantitative dynamical models that closely predict their behaviour. This study looks at a simple positive feedback circuit built by placing filamentous phage secretin pIV under a phage shock promoter. A single-equation ordinary differential equation model is developed to closely replicate the behaviour of the circuit, and its response to inhibition by TetR. A stepwise approach is employed to fit the model's parameters to time-series data for the circuit. This approach allows the dissection of the role of different parameters and leads to the identification of dependencies and redundancies between parameters. The developed genetic circuit and associated model may be used as a building block for larger circuits with more complex dynamics, which require tight quantitative control or tuning.
Zielonka D, Witkowski G, Puch EA, et al., 2020, Prevalence of non-psychiatric comorbidities in pre-symptomatic and symptomatic Huntington's disease gene carriers in Poland, Frontiers in Medicine, Vol: 7, ISSN: 2296-858X
Huntington's disease (HD) is monogenic neurodegenerative disorder caused by CAG expansions within the Huntingtin gene (Htt); it has a prevalence of 1 in 10,000 worldwide and is invariably fatal. Typically, healthy individuals have fewer than 35 CAG repeats, while the CAG expansions range from 36 to ~200 in HD patients. The hallmark of HD is neurodegeneration, especially in the striatal nuclei, basal ganglia and cerebral cortex, leading to neurological symptoms that involve motor, cognitive, and psychiatric events. However, HD is a complex disorder that may also affect peripheral organs, so it is possible that HD patients could be affected by comorbidities. Hence, we investigated the prevalence of comorbid conditions in HD patients (pre-symptomatic and symptomatic groups) and compared the frequency of those conditions to a control group. Our groups represent 65% of HD gene carriers registered in Poland. We identified 8 clusters of comorbid conditions in both HD groups, namely: musculoskeletal, allergies, cardiovascular, neurological, gastrointestinal, thyroid, psychiatric, and ophthalmologic. We found that HD patients have a significantly higher percentage of co-existing conditions in comparison to the control group. Among the 8 clusters of diseases, musculoskeletal, psychiatric, and cardiovascular events were significantly more frequent in both pre- and symptomatic HD patients, while neurological and gastrointestinal clusters showed significantly higher occurrence in the HD symptomatic group. A greater recognition of comorbidity in HD might help to better understand health outcomes and improve clinical management.
Scholes N, Schnoerr D, Isalan M, et al., 2019, A comprehensive network atlas reveals that Turing patterns are common but not robust, Cell Systems, Vol: 9, Pages: 243-257.e4, ISSN: 2405-4712
Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to distill design rules. We exhaustively analyze 2- and 3-node biological candidate Turing systems, amounting to 7,625 networks and more than 3 × 10^11 analyzed scenarios. We find that network structure alone neither implies nor guarantees emergent TPs. A large fraction (>61%) of network design space can produce TPs, but these are sensitive to even subtle changes in parameters, network structure, and regulatory mechanisms. This implies that TP networks are more common than previously thought, and evolution might regularly encounter prototypic solutions. We deduce compositional rules for TP systems that are almost necessary and sufficient (96% of TP networks contain them, and 92% of networks implementing them produce TPs). This comprehensive network atlas provides the blueprints for identifying natural TPs and for engineering synthetic systems.
Brödel A, Rodrigues R, Jaramillo A, et al., 2019, Engineering the smallest transcription factor: accelerated evolution of a 63-amino acid peptide dual activator-repressor
Transcription factors control gene expression in all life. This raises the question of what is the smallest protein that can support such activity. In nature, Cro from bacteriophage λ is the smallest known repressor (66 amino acids; a.a.) but activators are typically much larger (e.g. λ cI, 237 a.a.). Indeed, previous efforts to engineer a minimal activator from Cro resulted in no activity in vivo . In this study, we show that directed evolution results in a new Cro activator-repressor that functions as efficiently as λ cI, in vivo . To achieve this, we develop Phagemid-Assisted Continuous Evolution: PACEmid. We find that a peptide as small as 63-a.a. functions efficiently as an activator and/or repressor. To our knowledge, this is the smallest protein gene regulator reported to date, highlighting the capacity of transcription factors to evolve from very short peptide sequences.
Ciechonska M, Sturrock M, Grob A, et al., 2019, Ohm’s Law for increasing fitness gene expression with selection pressure
<jats:title>Abstract</jats:title><jats:p>Natural selection relies on genotypic and phenotypic adaptation in response to fluctuating environmental conditions and is the key to predicting and preventing drug resistance. Whereas classic persistence is all-or-nothing, here we show for the first time that an antibiotic resistance gene displays linear dose-responsive selection for increased expression in proportion to rising antibiotic concentration in <jats:italic>E. coli</jats:italic>. Furthermore, we observe the general nature of an instantaneous phenotypic selection process upon bactericidal and bacteriostatic antibiotic treatment, as well as an amino acid synthesis pathway enzyme under a range of auxotrophic conditions. To explain this phenomenon, we propose an analogy to Ohm’s law in electricity (V=IR) where fitness pressure acts similarly to voltage (V), gene expression to current (I), and resistance (R) to cellular machinery constraints. Lastly, mathematical modelling approaches reveal that the emergent gene expression mechanism requires variation in mRNA and protein production within an isogenic population, and cell ‘memory’ from positive feedbacks between growth and expression of any fitness-inducing gene.</jats:p>
Toczek M, Zielonka D, Marcinkowski J, et al., 2018, An altered metabolism of nucleotides leads to huntington’s disease related cardiomyopathy, EHDN Plenary Meeting, Publisher: BMJ Publishing Group, Pages: A13-A13, ISSN: 1468-330X
Schaerli Y, Jiménez A, Duarte JM, et al., 2018, Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution, Molecular Systems Biology, Vol: 14, ISSN: 1744-4292
Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.
Enrico Bena C, Grob A, Isalan M, et al., 2018, Commentary: Synthetic Addiction Extends the Productive Life Time of Engineered Escherichia coli Populations, Frontiers in Bioengineering and Biotechnology, Vol: 6, ISSN: 2296-4185
A commentary on Synthetic addiction extends the productive life time of engineered Escherichia coli populations by Rugbjerg, P., Sarup-Lytzen, K., Nagy, M., and Sommer, M. O. A. (2018). Proc. Natl. Acad. Sci. U.S.A. 115, 2347–2352. doi: 10.1073/pnas.1718622115Bioproduction is the process of producing added-value chemicals on large-scale using cells as biological factories. Cellular burden represents a significant problem in the scaling of fermentation processes from proof-of-concept to long-term cultures, as the load of heterologous gene expression and depletion of the cell intracellular resources cause unpredictable cellular physiological changes that can lead to decreased growth and lower production yields (Borkowski et al., 2016; Liu et al., 2018). One possible cause of the observed decreased bioproduct recovery in many bioprocessing applications is the accumulation of mutations in the employed genetic program. These mutations often lead to loss of production and rise of non-producing populations that grow better and easily overtake the growth of producing cells (Rugbjerg et al., 2018b).In a recent paper in PNAS, Rugbjerg et al. (2018b) developed a strategy to limit the enrichment of non-producing cell populations in bioproduction-employed cell cultures by placing the genes for key growth intermediates under the control of a promoter responsive to the bioproduct being made. This strategy known as product addiction was tested in E. coli engineered to produce mevalonic acid in long-term cultivations (Figure 1).
Critchley B, Isalan M, Mielcarek M, 2018, Neuro-Cardio mechanisms in Huntington’s disease and other neurodegenerative disorders, Frontiers in Physiology, Vol: 9, ISSN: 1664-042X
Although Huntington’s disease is generally considered to be aneurological disorder, there is mounting evidence that heart malfunction plays an important role in disease progression. This is perhaps not unexpected since both cardiovascular and nervous systems are strongly connected—both development ally and subsequently inhealth and disease. This connection occurs through a systemof central and peripheral neurons that control cardiovascular performance, while in return the cardiovascular system worksas a sensor for the nervous system to react to physiological events. Hence, given their permanent interconnectivity, any pathological events occurring in one system might affect the second. In addition, some pathological signals fromHuntington’s disease might occur simultaneously in both the cardiovascular and nervous systems, since mutant Huntingtin protein is expressedin both. Here we aim to review the source of HD-related cardiomyopathy in the light of recently-published studies, and to identify similarities between HD-related cardiomyopathy andother neuro-cardio disorders.
Kogenaru M, Isalan M, 2018, Drug-inducible control of lethality genes: a low background destabilizing domain architecture applied to the Gal4-UAS system in Drosophila, ACS Synthetic Biology, Vol: 7, Pages: 1496-1506, ISSN: 2161-5063
Destabilizing domains (DDs) are genetic tags that conditionally control the level of abundance of proteins-of-interest (POI) with specific stabilizing small-molecule drugs, rapidly and reversibly, in a wide variety of organisms. The amount of the DD-tagged fusion protein directly impacts its molecular function. Hence, it is important that the background levels be tightly regulated in the absence of any drug. This is especially true for classes of proteins that function at extremely low levels, such as lethality genes involved in tissue development and certain transcriptional activator proteins. Here, we establish the uninduced background and induction levels for two widely used DDs (FKBP and DHFR) by developing an accurate quantification method. We show that both DDs exhibit functional background levels in the absence of a drug, but each to a different degree. To overcome this limitation, we systematically test a double architecture for these DDs (DD-POI-DD) that completely suppresses the protein’s function in an uninduced state, while allowing tunable functional levels upon adding a drug. As an example, we generate a drug-stabilizable Gal4 transcriptional activator with extremely low background levels. We show that this functions in vivo in the widely used Gal4-UAS bipartite expression system in Drosophila melanogaster. By regulating a cell death gene, we demonstrate that only the low background double architecture enables tight regulation of the lethal phenotype in vivo. These improved tools will enable applications requiring exceptionally tight control of protein function in living cells and organisms.
Perez-Carrasco R, Barnes CP, Schaerli Y, et al., 2018, Combining a toggle switch and a repressilator within the AC-DC circuit generates distinct dynamical behaviors, Cell Systems, Vol: 6, Pages: 521-530.e3, ISSN: 2405-4712
Although the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors.
Grob A, Marbiah MM, Isalan M, 2018, Functional insulator scanning of CpG islands to identify regulatory regions of promoters using CRISPR, Methods in Molecular Biology, Vol: 1766, Pages: 285-301, ISSN: 1940-6029
The ability to mutate a promoter in situ is potentially a very useful approach for gaining insights into endogenous gene regulation mechanisms. The advent of CRISPR/Cas systems has provided simple, efficient, and targeted genetic manipulation in eukaryotes, which can be applied to studying genome structure and function.The basic CRISPR toolkit comprises an endonuclease, Cas9, and a short DNA-targeting sequence, made up of a single guide RNA (sgRNA). The catalytic domains of Cas9 are rendered active upon dimerization of Cas9 with sgRNA, resulting in targeted double stranded DNA breaks. Among other applications, this method of DNA cleavage can be coupled to endogenous homology-directed repair (HDR) mechanisms for the generation of site-specific editing or knockin mutations, at both promoter regulatory and gene coding sequences.A well-characterized regulatory feature of promoter regions is the high abundance of CpGs. These CpG islands tend to be unmethylated, ensuring a euchromatic environment that promotes gene transcription. Here, we demonstrate CRISPR-mediated editing of two CpG islands located within the promoter region of the MDR1 gene (Multi Drug Resistance 1). Cas9 is used to generate double stranded breaks across multiple target sites, which are then repaired while inserting the beta globin (β-globin) insulator, 5′HS5. Thus, we are screening through promoter regulatory sequences with a chromatin barrier element to identify functional regions via “insulator scanning.” Transcriptional and functional assessment of MDR1 expression provides evidence of genome engineering. Overall, this method allows the scanning of CpG islands to identify their promoter functions.
Broedel AK, Isalan M, 2018, Trp-ing upon new repressors, Nature Chemical Biology, Vol: 14, Pages: 328-329, ISSN: 1552-4450
Bioengineers have used directed evolution to generate a new family of synthetic transcription factors based on the tryptophan repressor. The evolved repressor family enables researchers to build new gene circuits for biomedical applications.
Broedel AK, Isalan M, Jaramillo A, 2017, Engineering of biomolecules by bacteriophage directed evolution, Current Opinion in Biotechnology, Vol: 51, Pages: 32-38, ISSN: 0958-1669
Conventional in vivo directed evolution methods have primarily linked the biomolecule's activity to bacterial cell growth. Recent developments instead rely on the conditional growth of bacteriophages (phages), viruses that infect and replicate within bacteria. Here we review recent phage-based selection systems for in vivo directed evolution. These approaches have been applied to evolve a wide range of proteins including transcription factors, polymerases, proteases, DNA-binding proteins, and protein–protein interactions. Advances in this field expand the possible applications of protein and RNA engineering. This will ultimately result in new biomolecules with tailor-made properties, as well as giving us a better understanding of basic evolutionary processes.
Schaerli Y, Jimenez A, Duarte J, et al., 2017, The mechanisms of gene regulatory networks constrain evolution: A lesson from synthetic circuits, Publisher: European Molecular Biology Organization
Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such restrictions are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most of the evidence for this is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in E. coli that produce a gene expression stripe; a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.
Broedel AK, Jaramillo A, Isalan M, 2017, Intracellular directed evolution of proteins from combinatorial libraries based on conditional phage replication, Nature Protocols, Vol: 12, Pages: 1830-1843, ISSN: 1750-2799
Directed evolution is a powerful tool to improve the characteristics of biomolecules. Here we present a protocol for the intracellular evolution of proteins with distinct differences and advantages in comparison with established techniques. These include the ability to select for a particular function from a library of protein variants inside cells, minimizing undesired coevolution and propagation of nonfunctional library members, as well as allowing positive and negative selection logics using basally active promoters. A typical evolution experiment comprises the following stages: (i) preparation of a combinatorial M13 phagemid (PM) library expressing variants of the gene of interest (GOI) and preparation of the Escherichia coli host cells; (ii) multiple rounds of an intracellular selection process toward a desired activity; and (iii) the characterization of the evolved target proteins. The system has been developed for the selection of new orthogonal transcription factors (TFs) but is capable of evolving any gene—or gene circuit function—that can be linked to conditional M13 phage replication. Here we demonstrate our approach using as an example the directed evolution of the bacteriophage λ cI TF against two synthetic bidirectional promoters. The evolved TF variants enable simultaneous activation and repression against their engineered promoters and do not cross-react with the wild-type promoter, thus ensuring orthogonality. This protocol requires no special equipment, allowing synthetic biologists and general users to evolve improved biomolecules within ~7 weeks.
Piotrowska I, Isalan M, Mielcarek ML, 2017, Early transcriptional alteration of histone deacetylases in a murine model of doxorubicin-induced cardiomyopathy, PLOS One, Vol: 12, ISSN: 1932-6203
Doxorubicin is a potent chemotherapeutic agent that is widely-used to treat a variety of cancers but causes acute and chronic cardiac injury, severely limiting its use. Clinically, the acute side effects of doxorubicin are mostly manageable, whereas the delayed consequences can lead to life-threatening heart failure, even decades after cancer treatment. The cardiotoxicity of doxorubicin is subject to a critical cumulative dose and so dosage limitation is considered to be the best way to reduce these effects. Hence, a number of studies have defined a “safe dose” of the drug, both in animal models and clinical settings, with the aim of avoiding long-term cardiac effects. Here we show that a dose generally considered as safe in a mouse model can induce harmful changes in the myocardium, as early as 2 weeks after infusion. The adverse changes include the development of fibrotic lesions, disarray of cardiomyocytes and a major transcription dysregulation. Importantly, low-dose doxorubicin caused specific changes in the transcriptional profile of several histone deacetylases (HDACs) which are epigenetic regulators of cardiac remodelling. This suggests that cardioprotective therapies, aimed at modulating HDACs during doxorubicin treatment, deserve further exploration.
Scholes NS, Isalan M, 2017, A three-step framework for programming pattern formation, Current Opinion in Chemical Biology, Vol: 40, Pages: 1-7, ISSN: 1879-0402
The spatial organisation of gene expression is essential to create structure and function in multicellular organisms during developmental processes. Such organisation occurs by the execution of algorithmic functions, leading to patterns within a given domain, such as a tissue. Engineering these processes has become increasingly important because bioengineers are seeking to develop tissues ex vivo. Moreover, although there are several theories on how pattern formation can occur in vivo, the biological relevance and biotechnological potential of each of these remains unclear. In this review, we will briefly explain four of the major theories of pattern formation in the light of recent work. We will explore why programming of such patterns is necessary, while discussing a three-step framework for artificial engineering approaches.
Mielcarek M, Smolenski RT, Isalan M, 2017, Transcriptional signature of an altered purine metabolism in the skeletal muscle of a Huntington’s disease mouse model, Frontiers in Physiology, Vol: 8, ISSN: 1664-042X
Huntington’s disease (HD) is a fatal neurodegenerative disorder,caused by a polyglutamine expansion in the huntingtin protein (HTT).HD has a peripheral component to its pathology: skeletal musclesare severely affected, leading to atrophy and malfunction in both pre-clinical and clinical settings. We previously used two symptomatic HD mouse models to demonstrate the impairment of the contractile characteristics of the hind limb muscles, which was accompanied by a significant loss of function of motor units. The mice displayed a significant reduction in muscle force, likely because of deteriorationsin energy metabolism, decreased oxidation and altered purine metabolism. There is growing evidence suggesting that HD-related skeletal muscle malfunction might be partially or completely independent of CNS degeneration. The pathology might arise from mutant HTT within muscle (loss or gain of function). Hence, it is vital to identify novel peripheral biomarkers that will reflect HD skeletal muscle atrophy. These will be important for upcoming clinical trials that may target HD peripherally. In order to identify potential biomarkers that might reflect muscle metabolic changes, we used qPCR to validate key gene transcripts in different skeletal muscle types. Consequently, we report a number of transcript alterations that are linked to HD muscle pathology.
Senthivel V, Sturrock M, Piedrafita G, et al., 2016, Identifying ultrasensitive HGF dose-response functions in a 3D mammalian system for synthetic morphogenesis, Scientific Reports, Vol: 6, ISSN: 2045-2322
Nonlinearresponses to signalsarewidespread natural phenomenathat affect various cellular processes. Nonlinearitycan bea desirable characteristic for engineering living organismsbecause it can lead to more switch-like responses, similar to those underlying the wiring inelectronics. Steeperfunctions are described as ultrasensitive, and can be applied in synthetic biologyby using various techniquesincludingreceptor decoys, multiple co-operative binding sites, and sequentialpositive feedbacks. Here, we explore the inherent non-linearity of a biological signaling system to identify functions that can potentially be exploited using cell genome engineering.For this,we performed genome-wide transcription profilingto identify genes with ultrasensitiveresponse functionsto Hepatocyte Growth Factor (HGF). Weidentified3,527genesthat react to increasing concentrations of HGF, in Madin-Darby canine kidney (MDCK) cells,grown as cystsin 3D collagen cell culture. By fitting a generic Hill function to the dose-responsesof these genes we obtained ameasure of the ultrasensitivityofHGF-responsive genes, identifying a subset with higher apparent Hill coefficients (e.g. MMP1, TIMP1,SNORD75, SNORD86 andERRFI1). The regulatory regions of these genes are potential candidates for future engineering of synthetic mammalian gene circuits requiring nonlinear responses to HGF signalling.
Broedel AK, Jaramillo A, Isalan M, 2016, Engineering orthogonal dual transcription factors for multi-input synthetic promoters, Nature Communications, Vol: 7, Pages: 1-9, ISSN: 2041-1723
Synthetic biology has seen an explosive growth in the capability of engineering artificial gene circuits from transcription factors (TFs), particularly in bacteria. However, most artificial networks still employ the same core set of TFs (for example LacI, TetR and cI). The TFs mostly function via repression and it is difficult to integrate multiple inputs in promoter logic. Here we present to our knowledge the first set of dual activator-repressor switches for orthogonal logic gates, based on bacteriophage λ cI variants and multi-input promoter architectures. Our toolkit contains 12 TFs, flexibly operating as activators, repressors, dual activator–repressors or dual repressor–repressors, on up to 270 synthetic promoters. To engineer non cross-reacting cI variants, we design a new M13 phagemid-based system for the directed evolution of biomolecules. Because cI is used in so many synthetic biology projects, the new set of variants will easily slot into the existing projects of other groups, greatly expanding current engineering capacities.
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