SynBioFromLeukipposInstitute

Cells receive many different environmental clues to which they must adapt accordingly. Therefore, a complex signal transduction network has evolved. Cellular signal transduction is a highly dynamic process, in which the specific outcome is a result of the exact spatial and temporal resolution of single sub-events. While conventional techniques, like chemical inducer systems, have led to a sound understanding of the architecture of signal transduction pathways, the spatiotemporal aspects were often impossible to resolve. Optogenetics, based on genetically encoded light-responsive proteins, has the potential to revolutionize manipulation of signal transduction processes. Light can be easily applied with highest precision and minimal invasiveness. This review focuses on examples of optogenetic systems which were generated and applied to manipulate non-neuronal mammalian signaling processes at various stages of signal transduction, from cell membrane through cytoplasm to nucleus. Further, the future of optogenetic signaling will be discussed.

A major goal of synthetic biology is to control cell behavior. RNA-mediated genetic switches (RNA switches) are devices that serve this purpose, as they can control gene expressions in response to input signals. In general, RNA switches consist of two domains: an aptamer domain, which binds to an input molecule, and an actuator domain, which controls the gene expression. An input binding to the aptamer can cause the actuator to alter the RNA structure, thus changing access to translation machinery. The assembly of multiple RNA switches has led to complex gene circuits for cell therapies, including the selective killing of pathological cells and purification of cell populations. The inclusion of RNA binding proteins, such as L7Ae, increases the repertoire and precision of the circuit. In this short review, we discuss synthetic RNA switches for gene regulation and their potential therapeutic applications.

Confining light to a cavity is often used to enhance the interaction between the light and a particle stored within the cavity. Benz et al. worked with a self-assembled monolayer of biphenyl-4-thiol molecules sandwiched between a gold film and a gold nanoparticle. They used laser irradiation to move atoms in the nanoparticle and produced a “picocavity” that was stable at cryogenic temperatures. The authors were then able to obtain time-dependent Raman spectra from individual molecules. Such subwavelength cavities that can localize light to volumes well below 1 nm3 will enable optical experiments on the atomic scale.

Synthetic biology is an engineering discipline that builds on our mechanistic understanding of molecular biology to program microbes to carry out new functions. Such predictable manipulation of a cell requires modeling and experimental techniques to work together. The modeling component of synthetic biology allows one to design biological circuits and analyze its expected behavior. The experimental component merges models with real systems by providing quantitative data and sets of available biological 'parts' that can be used to construct circuits. Sufficient progress has been made in the combined use of modeling and experimental methods, which reinforces the idea of being able to use engineered microbes as a technological platform.

Centromeres consist of specialized centrochromatin containing CENP-A nucleosomes intermingled with H3 nucleosomes carrying transcription-associated modifications. We have designed a novel synthetic biology 'in situ epistasis' analysis in which H3 dimethylated on lysine 4 (H3K4me2) demethylase LSD2 plus synthetic modules with competing activities are simultaneously targeted to a synthetic alphoidtetO HAC centromere. This allows us to uncouple transcription from histone modifications at the centromere. Here, we report that H3K4me2 loss decreases centromeric transcription, CENP-A assembly and stability and causes spreading of H3K9me3 across the HAC, ultimately inactivating the centromere. Surprisingly, CENP-28/Eaf6-induced transcription of the alphoidtetO array associated with H4K12 acetylation does not rescue the phenotype, whereas p65-induced transcription associated with H3K9 acetylation does rescue. Thus mitotic transcription plus histone modifications including H3K9ac constitute the 'epigenetic landscape' allowing CENP-A assembly and centrochromatin maintenance. H3K4me2 is required for the transcription and H3K9ac may form a barrier to prevent heterochromatin spreading and kinetochore inactivation at human centromeres.

Biomanufacturing is a type of manufacturing that utilizes biological systems (e.g., living microorganisms, resting cells, animal cells, plant cells, tissues, enzymes, or in vitro synthetic (enzymatic) systems) to produce commercially important biomolecules for use in the agricultural, food, material, energy, and pharmaceutical industries. History of biomanufacturing could be classified into the three revolutions in terms of respective product types (mainly), production platforms, and research technologies. Biomanufacturing 1.0 focuses on the production of primary metabolites (e.g., butanol, acetone, ethanol, citric acid) by using mono-culture fermentation; biomanufacturing 2.0 focuses on the production of secondary metabolites (e.g., penicillin, streptomycin) by using a dedicated mutant and aerobic submerged liquid fermentation; and biomanufacturing 3.0 focuses on the production of large-size biomolecules-proteins and enzymes (e.g., erythropoietin, insulin, growth hormone, amylase, DNA polymerase) by using recombinant DNA technology and advanced cell culture. Biomanufacturing 4.0 could focus on new products, for example, human tissues or cells made by regenerative medicine, artificial starch made by in vitro synthetic biosystems, isobutanol fermented by metabolic engineering, and synthetic biology-driven microorganisms, as well as exiting products produced by far better approaches. Biomanufacturing 4.0 would help address some of the most important challenges of humankind, such as food security, energy security and sustainability, water crisis, climate change, health issues, and conflict related to the energy, food, and water nexus.

With the recent industrial expansion, heavy metals and other pollutants have increasingly contaminated our living surroundings. Heavy metals, being non-degradable, tend to accumulate in the food chain, resulting in potentially damaging toxicity to organisms. Thus, techniques to detect metal ions have gradually begun to receive attention. Recent progress in research on synthetic biology offers an alternative means for metal ion detection via the help of promoter elements derived from microorganisms. To make the design easier, it is necessary to develop a systemic design method for evaluating and selecting adequate components to achieve a desired detection performance. A multi-objective (MO) H2/H∞ performance criterion is derived here for design specifications of a metal ion biosensor to achieve the H2 optimal matching of a desired input/output (I/O) response and simultaneous H∞ optimal filtering of intrinsic parameter fluctuations and external cellular noise. According to the two design specifications, a Takagi-Sugeno (T-S) fuzzy model is employed to interpolate several local linear stochastic systems to approximate the nonlinear stochastic metal ion biosensor system so that the multi-objective H2/H∞ design of the metal ion biosensor can be solved by an associated linear matrix inequality (LMI)-constrained multi-objective (MO) design problem. The analysis and design of a metal ion biosensor with optimal I/O response matching and optimal noise filtering ability then can be achieved by solving the multi-objective problem under a set of LMIs. Moreover, a multi-objective evolutionary algorithm (MOEA)-based library search method is employed to find adequate components from corresponding libraries to solve LMI-constrained MO H2/H∞ design problems. It is a useful tool for the design of metal ion biosensors, particularly regarding the tradeoffs between the design factors under consideration.

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control.