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Genetic Regulatory Mechanisms in the Synthesis of Proteins

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... Dynamics and progression of many fundamental processes in cells and organisms, including metabolism [1,2], the cell cycle [3], the circadian clock [4], differentiation [5,6] and development [7] are governed by GRNs. These networks generally control the activity of genes by regulatory motifs such as feedback or feed forward loops [8,9], which ensure spatially and temporally controlled gene expression. A striking property of gene transcription is its distinct stochastic behavior. ...
... The differential equations for the enzyme G that transforms M back into N are In Eqs. (8) and (9), the molecule numbers and fluxes that are synchronized at the end of each synchronization time step Δt are indicated with a circumflex accent. These parameters stay constant during each synchronization time step. ...
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Background The temporal progression of many fundamental processes in cells and organisms, including homeostasis, differentiation and development, are governed by gene regulatory networks (GRNs). GRNs balance fluctuations in the output of their genes, which trace back to the stochasticity of molecular interactions. Although highly desirable to understand life processes, predicting the temporal progression of gene products within a GRN is challenging when considering stochastic events such as transcription factor–DNA interactions or protein production and degradation. Results We report a method to simulate and infer GRNs including genes and biochemical reactions at molecular detail. In our approach, we consider each network element to be isolated from other elements during small time intervals, after which we synchronize molecule numbers across all network elements. Thereby, the temporal behaviour of network elements is decoupled and can be treated by local stochastic or deterministic solutions. We demonstrate the working principle of this modular approach with a repressive gene cascade comprising four genes. By considering a deterministic time evolution within each time interval for all elements, our method approaches the solution of the system of deterministic differential equations associated with the GRN. By allowing genes to stochastically switch between on and off states or by considering stochastic production of gene outputs, we are able to include increasing levels of stochastic detail and approximate the solution of a Gillespie simulation. Thereby, CaiNet is able to reproduce noise-induced bi-stability and oscillations in dynamically complex GRNs. Notably, our modular approach further allows for a simple consideration of deterministic delays. We further infer relevant regulatory connections and steady-state parameters of a GRN of up to ten genes from steady-state measurements by identifying each gene of the network with a single perceptron in an artificial neuronal network and using a gradient decent method originally designed to train recurrent neural networks. To facilitate setting up GRNs and using our simulation and inference method, we provide a fast computer-aided interactive network simulation environment, CaiNet. Conclusion We developed a method to simulate GRNs at molecular detail and to infer the topology and steady-state parameters of GRNs. Our method and associated user-friendly framework CaiNet should prove helpful to analyze or predict the temporal progression of reaction networks or GRNs in cellular and organismic biology. CaiNet is freely available at https://gitlab.com/GebhardtLab/CaiNet.
... Hybrid models, originally used by Glass (1975) (Glass, 1975) to construct a model of the synthesis of galactosidase in E. Coli and its regulation by lactose -originally discovered by Jacob and Monod (1961) (Jacob and Monod, 1961) -were developed as closely related to the Boolean models to generate a piecewise model of a gene regulatory system, in the absence of the biochemical information, in order to quantitatively and qualitatively explain the experimental observations. In these models, the variables of the piecewise linear differential equations (PLDE) represent the concentrations of the proteins, encoded from their respective genes, while the differential equations describe the regulating interactions, approximated as step functions (Casey, Jong and Gouzé, 2006). ...
... Hybrid models, originally used by Glass (1975) (Glass, 1975) to construct a model of the synthesis of galactosidase in E. Coli and its regulation by lactose -originally discovered by Jacob and Monod (1961) (Jacob and Monod, 1961) -were developed as closely related to the Boolean models to generate a piecewise model of a gene regulatory system, in the absence of the biochemical information, in order to quantitatively and qualitatively explain the experimental observations. In these models, the variables of the piecewise linear differential equations (PLDE) represent the concentrations of the proteins, encoded from their respective genes, while the differential equations describe the regulating interactions, approximated as step functions (Casey, Jong and Gouzé, 2006). ...
Conference Paper
Prior to the complexity risen form the large number of interacting components and the variety of the interactions within a biological system, discrete models – such as Boolean models, logical models, Petri nets, etc. – have been widely used, to highlight the system dynamics and stability. Regardless of their simplicity, these models can only give a qualitative description of the system properties, while they fail to describe quantitatively the system behaviour under internal/external perturbations. To bridge the gap between continuous and the discrete models, hybrid models have been developed, for a better description of the system behaviour. In this work, we give a comparison of the dynamical characteristics of these two approaches, applied on the Klotho gene – usually referred as the youth gene – with a special focus on its role on calcium and phosphate metabolism. The numerical results show the efficiency of the discrete and hybrid models to give qualitative information about the dynamics and stability of a gene regulatory system, when its kinetics is unknown (or partially known) and highlight the importance of this information, for a more detailed analysis and understanding of the system behaviour.
... A configuration x = (x 1 , ..., x n ) of the system is an assignment of a truth value x i ∈ {0, 1} to each element i of V . The set of all configurations (Jacob and Monod 1978), also called the space of configurations, is denoted by X = {0, 1} n . The dynamics of such a system is modeled via both a function f , called the global transition function, and an updating mode that defines how the elements of V are updated along time. ...
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Boolean dynamical systems (BDSs) represent the evolution of interactions inside a finite network of entities taking Boolean states over discrete time. These networks are classically used to model interactions of biological networks. In this context, a genetic network can be represented by both a Transition Graph (TG) and an Interaction Graph (IG). The precise relationship between IG and TG has been studied for many years in dynamical systems theory while still an open question. The global purpose of this article is to further study this relationship via a logical representation of BDSs into a nonmonotonic modal logic called Hypothesis Logic (H). While the dynamics of a BDS are characterized by a function f , an important part of the studies focused on the analysis of both stable configurations (i.e. fixed points of f), and stable/unstable cycles of f. For the representation of some genetic networks with no negative feedback circuits, results were previously obtained with some well known nonmono-tonic formalisms. So far however, BDSs representation by most of these formalisms does not permit to capture cyclic dynamical behaviors. Notably, the equivalent of a negative circuit has no extension in default logic (DL). This is embarrassing because these cycles may represent real interactions in living organisms like the cell cycle. This possible lack of extensions in DL was studied in H, for which theories always have extensions while some of these, called ghost extensions, are actually not extensions of the corresponding theories in DL. This paper addresses to the question of a first representation of the dynamics of BDSs with H, and ghost extensions appear to be a powerful tool in this respect. As we are especially concerned with cycles, it provides us with hints of simple algorithms for computing exhaustively both stable/unstable cycles and fixed points: distinguishing between stable/unstable as well as enumerating all the solutions in practice would be a major advance that would lead to apprehend better inner fundamental aspects in biology.
... When the Tn5-inactivated genes were complemented by a pUHE21-2 lacI q vector harboring each corresponding gene, the sensitivity of Pcc27 against POP72 was partially or completely restored even without IPTG induction ( Figure 3A). Complementation without IPTG induction, as well as the partial restoration, might be due to the improper levels of each protein within a bacterial cell because it is difficult to fine-tune the expression levels of genes with the leaky inducible lac promoter and IPTG (Jacob and Monod, 1978). The inframe wzc gene deletion mutant was also constructed and tested for the phage susceptibility. ...
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The emergence and widespread nature of pathogen resistance to antibiotics and chemicals has led to the re-consideration of bacteriophages as an alternative biocontrol agent in several fields, including agriculture. In this study, we isolated and characterized a novel bacteriophage, POP72, that specifically infects Pectobacterium carotovorum subsp. carotovorum (Pcc), which frequently macerates agricultural crops. POP72 contains a 44,760 bp double-stranded DNA genome and belongs to the family Podoviridae. To determine the phage receptor for POP72, a random mutant library of Pcc was constructed using a Tn5 transposon and screened for resistance against POP72 infection. Most of the resistant clones had a Tn5 insertion in various genes associated with colanic acid (CA) biosynthesis. The phage adsorption rate and CA production decreased dramatically in the resistant clones. Complementation of the clones with the pUHE21-2 lacIq vector harboring genes associated with CA biosynthesis restored their sensitivity to POP72, as well as their ability to produce CA. These results suggest that CA functions as a novel phage receptor for POP72. The application of POP72 protected Chinese cabbage from Pcc infection, suggesting that phage POP72 would be an effective alternative antimicrobial agent to protect agricultural products from Pcc.
... Le premier réseau de gènes a été établi par Jacob et Monod et leur modèle de l'opéron (Jacob and Monod, 1961). Leur étude démontre qu'un nombre réduit de gènes peut atteindre plusieurs états d'équilibre différents selon des stimuli extérieurs. ...
Thesis
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La modification post-traductionnelle des protéines par SUMO (sumoylation) est un mécanisme essentiel de régulation de la fonction des protéines et permet la coordination de larges programmes transcriptionnels. L'identité cellulaire repose sur des programmes transcriptionnels définis, soutenus par la configuration chromatinienne sous-jacente. Au cours de ce projet, nous avons pu montrer que la sumoylation à la chromatine constitue un mécanisme clé de sauvegarde de l'identité cellulaire des cellules pluripotentes et somatiques. Ainsi, la diminution de la sumoylation améliore la reprogrammation vers la pluripotence in vitro et in vivo, la transdifférenciation mais aussi la différenciation dans un modèle de leucémie humaine. Dans les cellules souches pluripotentes ESC une hyposumoylation conduit à une conversion vers un état proche de la totipotence (cellules « 2C-like »). Dans un deuxième temps nous avons caractérisé de manière endogène l’ensemble des protéines sumoylées (sumoylome) dans des fibroblastes et des cellules souches. Ces expériences ont révélé que SUMO modifie des larges réseaux de protéines physiquement associées. Le sumoylome des cellules ESC s’est révélé atypique : dans ces cellules la sumoylation affecte massivement les complexes répresseurs de la chromatine. De plus, nous avons pu montrer que la modification par SUMO des facteurs de pluripotence Dppa2 et Dppa4 est une barrière à la conversion vers l’état 2C-like. En résumé, cette étude a permis une meilleure compréhension des mécanismes stabilisant le destin cellulaire avec des applications potentielles en clinique notamment pour la médecine régénérative et le cancer.
... In 1961, Jacob and Monod provided a first glimpse into gene regulation with their famous publication on the mechanism controlling the expression of genes involved in lactose consumption in Escherichia coli (Jacob and Monod, 1961). A first important concept introduced in this work was the idea of bacterial genes being organized in operon; i.e. several genes involved in the same function, are placed under the control of a unique promoter and therefore co-transcribed into a single polycistronic RNA ( Figure 2 model II). ...
Thesis
RNA is a key molecule in gene expression and its regulation. Therefore, being able to monitor RNA through live-cell imaging would represent an important step toward a better understanding of gene expression regulation. RNA-based fluorogenic modules are extremely promising tools to reach this goal. To this end, two light-up RNA aptamers (Spinach and Mango) display attractive properties but they suffer from a limited brightness. Since previous work in the group demonstrated the possibility to evolve RNA using microfluidic-assisted in vitro compartmentalization (µIVC), this technology appeared to be well suited to improve light-up aptamers properties by an evolution strategy. Therefore, the µIVC procedure was adapted to fluorogenic RNA aptamers to improve their properties (especially the brightness). Finally, using µIVC in tandem with high-throughput sequencing (NGS) allowed further developing the technology into a more integrated and semi-automatized approach in which RNAs and biosensors are selected by µIVC screening and the best variants identified by a bioinformatics process upon NGS analysis. To summarize, this thesis allowed establishing robust µIVC screening workflows for the discovery of novel efficient light-up RNA aptamers as well as metabolites biosensors.
... Downloaded from locating mRNA in animal cells. First, mRNA in bacteria represents a small proportion of the total cellular RNA, and it is rapidly synthesized and degraded (9,38,51). Therefore, if bacterial cells are exposed to labeled RNA precursors for only a brief period, then the amount of radioactivity in mRNA relative to rRNA and tRNA is high enough so that mRNA can be studied as a radioactive RNA species. Second, rRNA represents a distinct species of RNA and does not therefore necessarily reflect the average composition of the total cell DNA; mRNA, on the other hand, comes from many genes and reflects the average DNA composition (92). ...
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Much of the research in biology aims to understand the origin of diversity. Naturally, ecological diversity was the first object of study, but we now have the necessary tools to probe diversity at molecular scales. The inherent differences in how we study diversity at different scales caused the disciplines of biology to be organized around these levels, from molecular biology to ecology. Here we illustrate that there are key properties of each scale that emerge from the interactions of simpler components and that these properties are often shared across different levels of organization. This means that ideas from one level of organization can be an inspiration for novel hypotheses to study phenomena at another level. We illustrate this concept with examples of events at the molecular level that have analogs at the organismal or ecological level and vice versa. Through these examples, we illustrate that biological processes at different organization levels are governed by general rules. The study of the same phenomena at different scales could enrich our work through a multidisciplinary approach, which should be a staple in the training of future scientists.
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Despite enormous progress in understanding the fundamentals of bacterial gene regulation, our knowledge remains limited when compared with the number of bacterial genomes and regulatory systems to be discovered. Derived from a small number of initial studies, classic definitions for concepts of gene regulation have evolved as the number of characterized promoters has increased. Together with discoveries made using new technologies, this knowledge has led to revised generalizations and principles. In this Expert Recommendation, we suggest precise, updated definitions that support a logical, consistent conceptual framework of bacterial gene regulation, focusing on transcription initiation. The resulting concepts can be formalized by ontologies for computational modelling, laying the foundation for improved bioinformatics tools, knowledge-based resources and scientific communication. Thus, this work will help researchers construct better predictive models, with different formalisms, that will be useful in engineering, synthetic biology, microbiology and genetics. In this Expert Recommendation, the authors review the definitions of classic concepts relating to bacterial gene regulation, with a focus on transcription initiation, and suggest up-to-date, precise definitions to provide a reference for knowledge representation, modelling and future research on bacterial gene regulation.
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Synthetic biology strives to reliably control cellular behavior, typically in the form of user-designed interactions of biological components to produce a predetermined output. Engineered circuit components are frequently derived from natural sources and are therefore often hampered by inadvertent interactions with host machinery, most notably within the host central dogma. Reliable and predictable gene circuits require the targeted reduction or elimination of these undesirable interactions to mitigate negative consequences on host fitness and develop context-independent bioactivities. Here, we review recent advances in biological orthogonalization, namely the insulation of researcher-dictated bioactivities from host processes, with a focus on systematic developments that may culminate in the creation of an orthogonal central dogma and novel cellular functions.
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Biomolecular computing is the field of engineering where computation, storage, communication, and coding are obtained by exploiting interactions between biomolecules, especially DNA, RNA, and enzymes. They are a promising solution in a long-term vision, bringing huge parallelism and negligible power consumption. Despite significant efforts in taking advantage of the massive computational power of biomolecules, many issues are still open along the way for considering biomolecular circuits as an alternative or a complement to competing with complementary metal–oxide–semiconductor (CMOS) architectures. According to the Von Neumann architecture, computing systems are composed of a central processing unit, a storage unit, and input and output (I/O). I/O operations are crucial to drive and read the computing core and to interface it to other devices. In emerging technologies, the complexity overhead and the bottleneck of I/O systems are usually limiting factors. While computing units and memories based on biomolecular systems have been successfully presented in literature, the published I/O operations are still based on laboratory equipment without a real development of integrated I/O. Biosensors are suitable devices for transducing biomolecular interactions by converting them into electrical signals. In this work, we explore the latest advancements in biomolecular computing, as well as in biosensors, with focus on technology suitable to provide the required and still missing I/O devices. Therefore, our goal is to picture out the present and future perspectives about DNA, RNA, and enzymatic-based computing according to the progression in its I/O technologies, and to understand how the field of biosensors contributes to the research beyond CMOS.
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Genetic analysis of bacteriophage and bacteria, particularly Escherichia coli , was a key to identifying DNA as the genetic material in the middle of the twentieth century, laying the foundations for the modern science of molecular biology in the process. Key experiments have become textbook classics, and most of those who performed them won Nobel Prizes for their work. The techniques that they developed, particularly conjugation and transduction, are still used in bacterial strain construction and for mapping of mutant genes. The advantages of large population size and rapid growth, combined with modern techniques of genome sequencing, the use of green fluorescent protein to measure gene expression and protein localisation, and one‐step strain construction will ensure that Escherichia coli remains central to answering the big biological questions of the twenty‐first century. Key Concepts • Escherichia coli and bacteriophage genetics enabled the identification of DNA as the genetic material in the mid‐twentieth century. • Key experiments conducted by Luria and Delbrück; Hershey and Chase; Avery, MacLeod and McCarty are textbook classics. • The first step towards understanding how gene expression is controlled came from Jacob and Monod's genetic studies of the Escherichia coli lac operon. • The genetic techniques of sexual conjugation and bacteriophage‐mediated transduction, pioneered by Joshua and Esther Lederberg, were the primary tools for chromosomal gene mapping and strain construction in Escherichia coli until recently. • Well‐characterised genetics combined with large population numbers and rapid growth ensure that Escherichia coli will remain a favourite model organism for scientists tackling the big biological questions of the twenty‐first century.
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This Reflections article is focused on the 5 years while I was a graduate student (1964-69). During this period, I made some of the most significant discoveries of my career. I have written this article primarily for a protein biochemistry audience, for my colleagues who shared this exciting time in science, and for the many scientists over the last 50 years who have contributed to our knowledge of transcriptional machinery and their regulation. It is also written for today’s graduate students, postdocs, and scientists who may not know much about the discoveries and technical advances that are now taken for granted, to show that even with methods primitive by today’s standards, we were still able to make foundational advances. I also hope to provide a glimpse into how fortunate I was to be a graduate student over 50 years ago in the golden age of molecular biology.
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Mechanotransduction describes activation of gene expression by changes in the cell's physical microenvironment. Recent experiments show that mechanotransduction can lead to long-term "mechanical memory", where cells cultured on stiff substrates for sufficient time (priming phase) maintain altered phenotype after switching to soft substrates (dissipation phase), as compared to unprimed controls. The timescale of memory acquisition and retention is orders of magnitude larger than the timescale of mechanosensitive cellular signaling, and memory retention time changes continuously with priming time. We develop a model that captures these features by accounting for positive reinforcement in mechanical signaling. The sensitivity of reinforcement represents the dynamic transcriptional state of the cell composed of protein lifetimes and 3D chromatin organization. Our model provides a single framework connecting microenvironment mechanical history to cellular outcomes ranging from no memory to terminal differentiation. Predicting cellular memory of environmental changes can help engineer cellular dynamics through changes in culture environments.
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Coordinated spatiotemporal expression of large sets of genes is required for the development and homeostasis of organisms. To achieve this goal, organisms use myriad strategies where they form operons, utilize bidirectional promoters, cluster genes, share enhancers among genes by DNA looping, and form topologically associated domains and transcriptional condensates. Coexpression achieved by these different strategies is hypothesized to have functional importance in minimizing gene expression variability, establishing dosage balance to ensure stoichiometry of protein complexes, and minimizing accumulation of toxic intermediate metabolites. By combining gene-editing tools with computational modeling, recent studies tested the advantages of adjacent genes located in pairs and clusters. We propose that with the advancement of gene editing, single-cell sequencing, and imaging tools, one could readily test the functional importance of different coexpression strategies in a variety of biological processes.
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Taking into account the spatial diffusion effect, this paper deals with the stability problem of genetic regulatory networks with both time-varying discrete delays (DDs) and distributed delays (DTDs). By virtue of the theories of delayed partial differential equation and Lyapunov stability, new algebraic conditions are established to guarantee the global exponential stability of the genetic regulatory networks with spatial diffusion (SDGRNs) with time-varying hybrid delays. The obtained conditions are generalized and easily calculated based on the system parameters. Besides, some extended results are presented for SDGRNs without diffusion effect or DTDs. Finally, the effectiveness and feasibility of the theoretical results are illustrated by two numerical examples and the corresponding simulation results.
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Neurodevelopmental disorders (NDDs) are a heterogeneous and highly prevalent group of psychiatric conditions marked by impairments in the nervous system. Their onset occurs during gestation, and the alterations are observed throughout the postnatal life. Although many genetic and environmental risk factors have been described in this context, the interactions between them challenge the understanding of the pathways associated with NDDs. Transcription factors (TFs) – a group of over 1,600 proteins that can interact with DNA, regulating gene expression through modulation of RNA synthesis, represent a point of convergence for different risk factors. In addition, TFs organize critical processes like angiogenesis, blood‐brain barrier formation, myelination, neuronal migration, immune activation, and many others in a time and location‐dependent way. In this review, we summarize important TF alterations in NDD and associated disorders, along with specific impairments observed in animal models, and, finally, establish hypotheses to explain how these proteins may be critical mediators in the context of genome‐environment interactions.
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CRISPR-associated proteins (Cas1 and Cas2) integrate foreign DNA at the “leader” end of CRISPR loci. Several CRISPR leader sequences are reported to contain a binding site for a DNA-bending protein called integration host factor (IHF). IHF-induced DNA bending kinks the leader of type I-E CRISPRs, recruiting an upstream sequence motif that helps dock Cas1-2 onto the first repeat of the CRISPR locus. To determine the prevalence of IHF-directed CRISPR adaptation, we analyzed 15,274 bacterial and archaeal CRISPR leaders. These experiments reveal multiple IHF binding sites and diverse upstream sequence motifs in a subset of the I-C, I-E, I-F, and II-C CRISPR leaders. We identify subtype-specific motifs and show that the phase of these motifs is critical for CRISPR adaptation. Collectively, this work clarifies the prevalence and mechanism(s) of IHF-dependent CRISPR adaptation and suggests that leader sequences and adaptation proteins may coevolve under the selective pressures of foreign genetic elements like plasmids or phages.
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In 1961, Francis Crick and Sydney Brenner, together with two Cambridge colleagues, published an article in Nature that used simple genetic experiments to demonstrate that the genetic code was almost certainly based on groups of three nucleotides. Six decades later, this article continues to be an inspiration to scientists due to its elegant argumentation and its use of simple, powerful experimentation to reveal fundamental truths about the organisation of living matter. This essay explores how and why the research was carried out, showing how the aims of the experiment gradually changed over time, and highlighting how the intense intellectual interactions between Crick and Brenner contributed to this model of scientific endeavour.
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Metaphors involve immense explanatory power and positive impact predominantly in the scientific education and popularization. Still the use of metaphors in science might be a double-edged sword. Introduction of the computer metaphor to many scientific fields in the last century resulted in reductionist approaches, oversimplifications and mechanistic explanations in science as well as in humanities. In this short commentary we developed further the computer metaphor by prof. Noble and the illusions this metaphor led to in genetics, linguistics and consequently DNA linguistics.
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Genomic DNA is replicated every cell cycle by the programmed activation of replication origins at specific times and chromosomal locations. The factors that define the locations of replication origins and their typical activation times in eukaryotic cells are poorly understood. Previous studies highlighted the role of activating factors and epigenetic modifications in regulating replication initiation. Here, we review the role that repressive pathways – and their alleviation – play in establishing the genomic landscape of replication initiation. Several factors mediate this repression, in particular, factors associated with inactive chromatin. Repression can support organized, yet stochastic, replication initiation, and its absence could explain instances of rapid and random replication or re-replication.
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In this chapter, the author envisages a scene in which the embryologist Conrad Hal Waddington is sitting atop a mountain, looking out over the city of Edinburgh, contemplating form. Although the concept of epigenetics has adopted many different forms with an explosion over the last few decades, he argues that Waddington's influence continues to inspire modern thinking about form and the structure and function of the genome. The eukaryotic nucleus contains territories for specific chromosomes and these territories are organized into chromosome compartments of “active” or “inactive” chromatin. By bringing together genetics and developmental biology, Waddington reintroduced thinking about epigenesis, about the emergence of form over time through the interactions between constituent parts. This led to the evolution of a landscape metaphor to describe the cell‐fate determination over developmental time.
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The Modern Synthesis has dominated biology for 80 years. It was formulated in 1942, a decade before the major achievements of molecular biology, including the Double Helix and the Central Dogma. When first formulated in the 1950s these discoveries and concepts seemed initially to completely justify the central genetic assumptions of the Modern Synthesis. The Double Helix provided the basis for highly accurate DNA replication, while the Central Dogma was viewed as supporting the Weismann Barrier, so excluding the inheritance of acquired characteristics. This article examines the language of the Modern Synthesis and reveals that it is based on four important misinterpretations of what molecular biology had shown, so forming the basis of the four Illusions: 1. Natural Selection; 2. The Weismann Barrier; 3. The Rejection of Darwin’s Gemmules; 4. The Central Dogma. A multi-level organisation view of biology avoids these illusions through the principle of biological relativity. Molecular biology does not therefore confirm the assumptions of the Modern Synthesis.
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How populations distribute in both space and time is one of the key issues in ecological systems, which can characterize the relationship between populations, space–time structure and evolution law. Consequently, pattern dynamics in ecosystems has been widely investigated including their causes and ecological functions. In order to systematically understand the interactions in ecosystems, we summarize the related results in pattern formation of ecological systems. Based on mathematical modeling and analysis, we show the mechanisms of different patterns including feedback, scale-dependent, phase separation, nonlocal effects, time delay and spatial heterogeneity. This work offers assistance for better understanding the complexity of ecosystems and provides new insights for self-organizations evolution and ecosystem protection. We hope that our results may be applied in other related fields such as epidemiology, medical science, atmospheric science and so on.
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Prokaryote genomics started in earnest in 1995, with the complete sequences of two small bacterial genomes, those of Haemophilus influenzae and Mycoplasma genitalium. During the next quarter century, the prokaryote genome database has been growing exponentially, with no saturation in sight. For most of these 25 years, genome sequencing remained limited to cultivable microbes. Together with next-generation sequencing methods, advances in metagenomics and single-cell genomics have lifted this limitation, providing for an increasingly unbiased characterization of the global prokaryote diversity. Advances in computational genomics followed the progress of genome sequencing, even if occasionally lagging behind. Several major new branches of bacteria and archaea were discovered, including Asgard archaea, the apparent closest relatives of eukaryotes and expansive groups of bacteria and archaea with small genomes thought to be symbionts of other prokaryotes. Comparative analysis of numerous prokaryote genomes spanning a wide range of evolutionary distances changed the conceptual foundations of microbiology, supplanting the notion of species genomes with fixed gene sets with that of dynamic pangenomes and the notion of a single Tree of Life (ToL) with a statistical tree-like trend among individual gene trees. Strides were also made towards a theory and quantitative laws of prokaryote genome evolution.
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The regulation of signalling capacity, combined with the spatiotemporal distribution of developmental signals themselves, is pivotal in setting developmental responses in both plants and animals¹. The hormone auxin is a key signal for plant growth and development that acts through the AUXIN RESPONSE FACTOR (ARF) transcription factors2–4. A subset of these, the conserved class A ARFs⁵, are transcriptional activators of auxin-responsive target genes that are essential for regulating auxin signalling throughout the plant lifecycle2,3. Although class A ARFs have tissue-specific expression patterns, how their expression is regulated is unknown. Here we show, by investigating chromatin modifications and accessibility, that loci encoding these proteins are constitutively open for transcription. Through yeast one-hybrid screening, we identify the transcriptional regulators of the genes encoding class A ARFs from Arabidopsis thaliana and demonstrate that each gene is controlled by specific sets of transcriptional regulators. Transient transformation assays and expression analyses in mutants reveal that, in planta, the majority of these regulators repress the transcription of genes encoding class A ARFs. These observations support a scenario in which the default configuration of open chromatin enables a network of transcriptional repressors to regulate expression levels of class A ARF proteins and modulate auxin signalling output throughout development.
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Control of the lac operon with isopropyl β-d-1-thiogalactopyranoside (IPTG) has been used to regulate gene expression in Escherichia coli for countless applications, including metabolic engineering and recombinant protein production. However, optogenetics offers unique capabilities, such as easy tunability, reversibility, dynamic induction strength and spatial control, that are difficult to obtain with chemical inducers. We have developed a series of circuits for optogenetic regulation of the lac operon, which we call OptoLAC, to control gene expression from various IPTG-inducible promoters using only blue light. Applying them to metabolic engineering improves mevalonate and isobutanol production by 24% and 27% respectively, compared to IPTG induction, in light-controlled fermentations scalable to at least two-litre bioreactors. Furthermore, OptoLAC circuits enable control of recombinant protein production, reaching yields comparable to IPTG induction but with easier tunability of expression. OptoLAC circuits are potentially useful to confer light control over other cell functions originally designed to be IPTG-inducible.
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Though it goes without saying that linear algebra is fundamental to mathematical biology, polynomial algebra is less visible. In this article, we will give a brief tour of four diverse biological problems where multivariate polynomials play a central role—a subfield that is sometimes called algebraic biology. Namely, these topics include biochemical reaction networks, Boolean models of gene regulatory networks, algebraic statistics and genomics, and place fields in neuroscience. After that, we will summarize the history of discrete and algebraic structures in mathematical biology, from their early appearances in the late 1960s to the current day. Finally, we will discuss the role of algebraic biology in the modern classroom and curriculum, including resources in the literature and relevant software. Our goal is to make this article widely accessible, reaching the mathematical biologist who knows no algebra, the algebraist who knows no biology, and especially the interested student who is curious about the synergy between these two seemingly unrelated fields.
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Here, we describe a free, web‐based simulation of the lac operon, “LacOp,” that is designed to enhance the learning of prokaryotic gene regulation and pathways in advanced high school and undergraduate genetics courses. This new electronic resource was created by a team of students in an advanced undergraduate course and is hosted online (http://flask-env.rnwhymamqf.us-west-2.elasticbeanstalk.com/lacop). LacOp has a simple web interface compatible with a range of devices, including smartphones. To determine whether the LacOp simulation enhances student learning from traditional instruction, we introduced the lac operon to undergraduate genetics students through a traditional classroom experience followed by use of the LacOp simulation. Students worked on their own using the included tutorial to create and test the effect of various genotypes on E. coli lactose metabolism and regulation. Upon completion of the tutorial, students showed measurable gains in conceptual understanding of the lac operon. These students also reported a generally favorable opinion of the LacOP simulation as a use of their instructional time.
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Gene regulatory networks evolve through rewiring of individual components-that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor-DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor-DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.
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Die genetische und biochemische Untersuchung des Systems, das bei Escherichia coli für die Synthese der β-Galactosidase verantwortlich ist, ergab, daß die Fähigkeit zur Enzymsynthese von einem Gen bestimmt wird, das offenbar die gesamte Information über die Struktur des Proteinmoleküls enthält. Ein zweites Gen, dem ersten unmittelbar benachbart, aber von ihm funktionell unabhängig, steuert die Bildung eines Repressors, dessen Aufgabe es ist, die Aktivität des galactosidase-synthetisierenden Systems zu hemmen. Extrazelluläre Induktoren, welche die Synthese des Enzyms stimulieren, wirken als Antagonisten des intrazellulären Repressors.