An efficient platform for genetic selection and screening of gene switches in Escherichia coli

Engineered gene switches and circuits that can sense various biochemical and physical signals, perform computation, and produce predictable outputs are expected to greatly advance our ability to program complex cellular behaviors. However, rational design of gene switches and circuits that function in living cells is challenging due to the complex intracellular milieu. Consequently, most successful designs of gene switches and circuits have relied, to some extent, on high-throughput screening and/or selection from combinatorial libraries of gene switch and circuit variants. In this study, we describe a generic and efficient platform for selection and screening of gene switches and circuits in Escherichia coli from large libraries. The single-gene dual selection marker tetA was translationally fused to green fluorescent protein (gfpuv) via a flexible peptide linker and used as a dual selection and screening marker for laboratory evolution of gene switches. Single-cycle (sequential positive and negative selections) enrichment efficiencies of >7000 were observed in mock selections of model libraries containing functional riboswitches in liquid culture. The technique was applied to optimize various parameters affecting the selection outcome, and to isolate novel thiamine pyrophosphate riboswitches from a complex library. Artificial riboswitches with excellent characteristics were isolated that exhibit up to 58-fold activation as measured by fluorescent reporter gene assay.     

Atelocollagen-based gene transfer in cells allows high-throughput screening of gene functions.

We have previously demonstrated that Atelocollagen, used clinically for wound healing, is a reliable safe carrier for gene delivery. To obtain phenotypic changes by gene expression of cDNA, we developed an efficient technique for high-throughput gene transfer and expression screening in mammalian cells in microarrays by precoating a microplate with an Atelocollagen complexed with cDNA to which cells are then seeded. The complexes with a nanoparticle form were efficiently transduced into cells without use of any additional transfection reagent, and they allowed for long-term gene expression without apparent chromosomal integration. The complex spotted onto the well of a microplate was stable for a long period and allowed the cells to transduce and express reporter genes in a dose-dependent manner. We also showed that the present method using Atelocollagen-based gene transfer is applicable to gene medicines such as antisense ODNs and adenovirus vectors. These results suggest that Atelocollagen may be appropriate for general use in high-throughput screening of large sets of gene medicines for functional analyses in mammalian cells.     

Synthetic therapeutic gene circuits in mammalian cells

In the emerging field of synthetic biology, scientists are focusing on designing and creating functional devices, systems, and organisms with novel functions by engineering and assembling standardised biological building blocks. The progress of synthetic biology has significantly advanced the design of functional gene networks that can reprogram metabolic activities in mammalian cells and provide new therapeutic opportunities for future gene- and cell-based therapies. In this review, we describe the most recent advances in synthetic mammalian gene networks designed for biomedical applications, including how these synthetic therapeutic gene circuits can be assembled to control signalling networks and applied to treat metabolic disorders, cancer, and immune diseases. We conclude by discussing the various challenges and future prospects of using synthetic mammalian gene networks for disease therapy.     

Computational design of synthetic regulatory networks from a genetic library to characterize the designability of dynamical behaviors

The engineering of synthetic gene networks has mostly relied on the assembly of few characterized regulatory elements using rational design principles. It is of outmost importance to analyze the scalability and limits of such a design workflow. To analyze the design capabilities of libraries of regulatory elements, we have developed the first automated design approach that combines such elements to search the genotype space associated to a given phenotypic behavior. Herein, we calculated the designability of dynamical functions obtained from circuits assembled with a given genetic library. By designing circuits working as amplitude filters, pulse counters and oscillators, we could infer new mechanisms for such behaviors. We also highlighted the hierarchical design and the optimization of the interface between devices. We dissected the functional diversity of a constrained library and we found that even such libraries can provide a rich variety of behaviors. We also found that intrinsic noise slightly reduces the designability of digital circuits, but it increases the designability of oscillators. Finally, we analyzed the robust design as a strategy to counteract the evolvability and noise in gene expression of the engineered circuits within a cellular background, obtaining mechanisms for robustness through non-linear negative feedback loops.     

Model‐guided combinatorial optimization of complex synthetic gene networks

Constructing gene circuits that satisfy quantitative performance criteria has been a long‐standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three‐gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high‐throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model‐guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.     

Engineering and control of biological systems: A new way to tackle complex diseases

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health.     

RNA干扰文库及其在功能基因组学研究中的应用

随着人类基因组大规模测序的完成,下一步的挑战是了解每一个基因的功能 . RNA 干扰文库为大规模基因功能筛选提供了可能 . 虽然用于线虫等模式生物的 RNAi 文库,已经证明是大规模基因功能筛选的有效方法,但这些文库不能用于高等动物的细胞 . 自 2003 年以来,用于人的细胞和哺乳动物细胞的 RNAi 文库取得了突破,相继出现构建已知基因 RNAi 文库和构建随机 RNAi 文库的报道,并成功地应用于大规模基因功能的筛选 . RNAi 文库作为一种简单、高效、大规模、高通量的功能基因组学研究的工具,将在基因功能研究、发现新的药物靶基因、发现疾病相关基因等方面有广阔的应用前景 .     

Coherent activation of a synthetic mammalian gene network

A quantitative analysis of naturally-occurring regulatory networks, especially those present in mammalian cells, is difficult due to their high complexity. Much simpler gene networks can be engineered in model organisms and analyzed as isolated regulatory modules. Recently, several synthetic networks have been constructed in mammalian systems. However, most of these engineered mammalian networks have been characterized using steady-state population level measurements. Here, we use an integrated experimental-computational approach to analyze the dynamical response of a synthetic positive feedback network in individual mammalian cells. We observe a switch-like activation of the network with variable delay times in individual cells. In agreement with a stochastic model of the network, we find that increasing the strength of the positive feedback results in a decrease in the mean delay time and a more coherent activation of individual cells. Our results are important for gaining insight into biological processes which rely on positive feedback regulation.     

Hidden hysteresis – population dynamics can obscure gene network dynamics

Background

Positive feedback is a common motif in gene regulatory networks. It can be used in synthetic networks as an amplifier to increase the level of gene expression, as well as a nonlinear module to create bistable gene networks that display hysteresis in response to a given stimulus. Using a synthetic positive feedback-based tetracycline sensor in E. coli, we show that the population dynamics of a cell culture has a profound effect on the observed hysteretic response of a population of cells with this synthetic gene circuit.

Results

The amount of observable hysteresis in a cell culture harboring the gene circuit depended on the initial concentration of cells within the culture. The magnitude of the hysteresis observed was inversely related to the dilution procedure used to inoculate the subcultures; the higher the dilution of the cell culture, lower was the observed hysteresis of that culture at steady state. Although the behavior of the gene circuit in individual cells did not change significantly in the different subcultures, the proportion of cells exhibiting high levels of steady-state gene expression did change.Although the interrelated kinetics of gene expression and cell growth are unpredictable at first sight, we were able to resolve the surprising dilution-dependent hysteresis as a result of two interrelated phenomena - the stochastic switching between the ON and OFF phenotypes that led to the cumulative failure of the gene circuit over time, and the nonlinear, logistic growth of the cell in the batch culture.

Conclusions

These findings reinforce the fact that population dynamics cannot be ignored in analyzing the dynamics of gene networks. Indeed population dynamics may play a significant role in the manifestation of bistability and hysteresis, and is an important consideration when designing synthetic gene circuits intended for long-term application.

     

Mapping signal transduction pathways by phage display

Rapid identification of proteins that interact with a novel gene product is an important element of functional genomics. Here we describe a phage display-based technique for interaction screening of complex cDNA libraries using proteins or synthetic peptides as baits. Starting with the epidermal growth factor receptor (EGFR) cytoplasmic tail, we identified known protein interactions that link EGFR to the Ras/MAP kinase signal transduction cascade and several novel interactions. This approach can be used as a rapid and efficient tool for elucidating protein networks and mapping intracellular signal transduction pathways.