94 results found
Ledesma Amaro R, Selles Vidal L, Isalan M, et al., 2023, A primer to directed evolution: current methodologies and future directions, RSC Chemical Biology, Pages: 1-21, ISSN: 2633-0679
Directed evolution is one of the most powerful tools for protein engineering and functions by harnessing natural evolution, but on a shorter timescale. It enables the rapid selection of variants of biomolecules with properties that make them more suitable for specific applications. Since the first in vitro evolution experiments performed by Sol Spiegelman in 1967, a wide range of techniques have been developed to tackle the main two steps of directed evolution: genetic diversification (library generation), and isolation of the variants of interest. This review covers the main modern methodologies, discussing the advantages and drawbacks of each, and hence the considerations for designing directed evolution experiments. Furthermore, the most recent developments are discussed, showing how advances in the handling of ever larger library sizes are enabling new research questions to be tackled.
Bennett EM, Murray JW, Isalan M, 2023, Engineering Nitrogenases for synthetic nitrogen fixation: From pathway engineering to directed evolution, BioDesign Research, Vol: 5, Pages: 1-12, ISSN: 2693-1257
Globally, agriculture depends on industrial nitrogen fertilizer to improve crop growth. Fertilizer production consumes fossil fuels and contributes to environmental nitrogen pollution. A potential solution would be to harness nitrogenases—enzymes capable of converting atmospheric nitrogen N2 to NH3 in ambient conditions. It is therefore a major goal of synthetic biology to engineer functional nitrogenases into crop plants, or bacteria that form symbiotic relationships with crops, to support growth and reduce dependence on industrially produced fertilizer. This review paper highlights recent work toward understanding the functional requirements for nitrogenase expression and manipulating nitrogenase gene expression in heterologous hosts to improve activity and oxygen tolerance and potentially to engineer synthetic symbiotic relationships with plants.
Ciechonska M, Sturrock M, Grob A, et al., 2022, Emergent expression of fitness-conferring genes by phenotypic selection, PNAS Nexus, Vol: 1, Pages: 1-13, ISSN: 2752-6542
Genotypic and phenotypic adaptation is the consequence of ongoing natural selection in populations and is key to predicting and preventing drug resistance. Whereas classic antibiotic persistence is all-or-nothing, here we demonstrate that an antibiotic resistance gene displays linear dose-responsive selection for increased expression in proportion to rising antibiotic concentration in growing E. coli populations. Furthermore, we report the potentially wide-spread nature of this form of emergent gene expression by instantaneous phenotypic selection process under bactericidal and bacteriostatic antxibiotic treatment, as well as an amino acid synthesis pathway enzyme under a range of auxotrophic conditions. We propose an analogy to Ohm’s law in electricity (V=IR) where selection pressure acts similarly to voltage (V), gene expression to current (I), and resistance (R) to cellular machinery constraints and costs. Lastly, mathematical modelling using agent-based models of stochastic gene expression in growing populations and Bayesian model selection reveal that the emergent gene expression mechanism requires variability in gene expression within an isogenic population, and a cellular ‘memory’ from positive feedbacks between growth and expression of any fitness-conferring gene. Finally, we discuss the connection of the observed phenomenon to a previously described general fluctuation-response relationship in biology.
Oliver-Huidobro M, Tica J, Wachter G, et al., 2022, Synthetic spatial patterning in bacteria: advances based on novel diffusible signals, Microbial Biotechnology, Vol: 15, Pages: 1685-1694, 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.
Tica J, Davenport B, Isalan M, 2022, Reducing metabolic burden in the PACEmid evolver system by remastering high copy phagemid vectors, Engineering Biology, ISSN: 2398-6182
Orthogonal or non-cross-reacting transcription factors are used in synthetic biology as componentsof genetic circuits. Brödel et al. (2016) engineered 12 such cIλ transcription factor variants, using adirected evolution ‘PACEmid’ system. The variants operate as dual activator/repressors and expandgene circuit construction possibilities. However, the high-copy phagemid vectors carrying the cIλvariants imposed high metabolic burden upon cells. Here, we ‘remaster’ the phagemid backbones torelieve their burden substantially, exhibited by a recovery in E. coli growth. The remasteredphagemids’ ability to function within the PACEmid evolver system is maintained, as is the cIλtranscription factors’ activity within these vectors. The low-burden phagemid versions are moresuitable for use in PACEmid experiments and synthetic gene circuits; we have therefore replaced theoriginal high-burden phagemids on the Addgene repository. Our work emphasises the importance ofunderstanding metabolic burden and incorporating it into design steps in future synthetic biologyventures.
Mazur-Michałek I, Ruciński M, Sowiński M, et al., 2022, Identification of the transcriptional biomarkers panel linked to pathological remodelling of the eye tissues in various HD mouse models., Cells, Vol: 11, ISSN: 2073-4409
Ocular abnormalities are becoming associated with a spectrum of pathological events in various neurodegenerative diseases. Huntington’s disease (HD) is just such an example of a fatal neurological disorder, where mutated genes (CAG trinucleotide expansions in the Huntingtin gene) have widespread expression, leading to the production of mutant Huntingtin (mHTT) protein. It is well known that mutant HTT protein is prone to form toxic aggregates, which are a typical pathological feature, along with global transcriptome alterations. In this study, we employed well-established quantitative methods like Affymetrix arrays and quantitative PCR (qPCR) to identify a set of transcriptional biomarkers that will track HD progression in three well-established mouse models: R6/2, R6/1 and HdhQ150. Our array analysis revealed significantly deregulated networks that are related to visual processes and muscle contractions. Furthermore, our targeted quantitative analysis identified a panel of biomarkers with some being dysregulated even at the presymptomatic stage of the disease, e.g. Opn1mw, Opn1sw and Pfkfb2. Some of the deregulated genes identified in this study have been linked to other genetic ocular disorders like: GNAT2, a source of achromatopasia; and REEP6, linked to Retinitis pigmentosa. It may thus be a useful platform for preclinical evaluations of therapeutic interventions.
Mazur-Michałek I, Kowalska K, Zielonka D, et al., 2022, Structural abnormalities of the optic nerve and retina in Huntington’s disease pre-clinical and clinical settings, International Journal of Molecular Sciences, Vol: 23, ISSN: 1422-0067
Huntington’s disease (HD) is a fatal neurodegenerative disorder caused by a polyglutamine expansion in the huntingtin protein. HD-related pathological remodelling has been reported in HD mouse models and HD carriers. In this study, we studied structural abnormalities in the optic nerve by employing Spectral Domain Optical Coherence Tomography (SD-OCT) in pre-symptomatic HD carriers of Caucasian origin. Transmission Electron Microscopy (TEM) was used to investigate ultrastructural changes in the optic nerve of the well-established R6/2 mouse model at the symptomatic stage of the disease. We found that pre-symptomatic HD carriers displayed a significant reduction in the retinal nerve fibre layer (RNFL) thickness, including specific quadrants: superior, inferior and temporal, but not nasal. There were no other significant irregularities in the GCC layer, at the macula level and in the optic disc morphology. The ultrastructural analysis of the optic nerve in R6/2 mice revealed a significant thinning of the myelin sheaths, with a lamellar separation of the myelin, and a presence of myelonoid bodies. We also found a significant reduction in the thickness of myelin sheaths in peripheral nerves within the choroids area. Those ultrastructural abnormalities were also observed in HD photoreceptor cells that contained severely damaged membrane disks, with evident vacuolisation and swelling. Moreover, the outer segment of retinal layers showed a progressive disintegration. Our study explored structural changes of the optic nerve in pre- and clinical settings and opens new avenues for the potential development of biomarkers that would be of great interest in HD gene therapies.
Bell R, Clarke NK, Isalan M, et al., 2022, Regulated Expression of LentiviralVectors Following Administration of anInducing Molecule, 2022 ASGCT Annual Meeting, Publisher: Cell Press, Pages: 419-419, ISSN: 1525-0016
Racovita A, Prakash S, Varela C, et al., 2022, Engineered gene circuits capable of reinforcement learning allow bacteria to master gameplaying
<jats:title>Abstract</jats:title><jats:p>The engineering of living cells able to learn by themselves algorithms such as playing board games —a classic challenge for artificial intelligence— will allow complex ecosystems and tissues to be chemically reprogrammed to learn complex decisions. However, current engineered gene circuits encoding decision-making algorithms have failed to implement self-programmability and they require supervised tuning. We show a strategy for engineering gene circuits to rewire themselves by reinforcement learning. We created a scalable general-purpose library of <jats:italic>Escherichia coli</jats:italic> strains encoding elementary adaptive genetic systems capable of persistently adjusting their relative levels of expression according to their previous behavior. Our strains can learn the mastery of 3x3 board games such as tic-tac-toe from a <jats:italic>tabula rasa</jats:italic> state of complete ignorance. We provide a general genetic mechanism for the autonomous learning of decisions in changeable environments.</jats:p><jats:sec><jats:title>One-Sentence Summary</jats:title><jats:p>We propose a scalable strategy to engineer gene circuits capable of autonomously learning decision-making in complex environments.</jats:p></jats:sec>
Broto A, Gaspari E, Miravet-Verde S, et al., 2022, A genetic toolkit and gene switches to limit Mycoplasma growth for biosafety applications, Nature Communications, Vol: 13, ISSN: 2041-1723
Mycoplasmas have exceptionally streamlined genomes and are strongly adapted to their many hosts, which provide them with essential nutrients. Owing to their relative genomic simplicity, Mycoplasmas have been used to develop chassis for biotechnological applications. However, the dearth of robust and precise toolkits for genomic manipulation and tight regulation has hindered any substantial advance. Herein we describe the construction of a robust genetic toolkit for M. pneumoniae, and its successful deployment to engineer synthetic gene switches that control and limit Mycoplasma growth, for biosafety containment applications. We found these synthetic gene circuits to be stable and robust in the long-term, in the context of a minimal cell. With this work, we lay a foundation to develop viable and robust biosafety systems to exploit a synthetic Mycoplasma chassis for live attenuated vectors for therapeutic applications.
Bell RV, Clarke NK, Isalan M, et al., 2022, Regulated Expression of Lentiviral Vectors Following Administration of an Inducing Molecule, Publisher: CELL PRESS, Pages: 419-419, ISSN: 1525-0016
Au HKE, Isalan M, Mielcarek M, 2022, Gene therapy advances: a meta-analysis of AAV usage in clinical settings, Frontiers in Medicine, Vol: 8, Pages: 1-14, 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.
Bell RV, Isalan M, Alton EWFW, et al., 2021, Regulation of lentivirus‐mediated expression in a human airway model, ESGCT Collaborative Virtual Congress, Publisher: Mary Ann Liebert, ISSN: 1043-0342
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.
Broto A, Gaspari E, Miravet-Verde S, et al., 2021, A genetic toolkit and gene switches to limit Mycoplasma growth for a synthetic vaccine chassis
<jats:title>Abstract</jats:title> <jats:p><jats:italic>Mycoplasmas</jats:italic> have exceptionally streamlined genomes and are strongly adapted to their many hosts, which provide them with essential nutrients. Owing to their relative genomic simplicity, <jats:italic>Mycoplasmas</jats:italic> have been used for the development of chassis to deploy tailored vaccines. However, the dearth of robust and precise toolkits for genomic manipulation and tight regulation has hindered any substantial advance. Herein we describe the construction of a robust genetic toolkit for <jats:italic>M. pneumoniae</jats:italic>, and its successful deployment to engineer synthetic gene switches that control and limit <jats:italic>Mycoplasma</jats:italic> growth, for biosafety containment applications. We found these synthetic gene circuits to be stable and robust in the long-term, in the context of a minimal cell. With this work, we lay a foundation to develop viable and robust biosafety systems to exploit a synthetic <jats:italic>Mycoplasma</jats:italic> chassis for live attenuated vaccines or even for live vectors for biotherapeutics.</jats:p>
Isalan M, 2021, DNA recognition/processing: Zinc fingers: Structure and design, Encyclopedia of Biological Chemistry: Third Edition, Pages: 506-516, ISBN: 9780128194607
- Citations: 3
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 NS, 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: 515-517, ISSN: 2405-4712
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).
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