A programmable NOR-based device for transcription profile analysis

RNA Polymerase Tags To Monitor Multidimensional Protein-Protein Interactions Reveal Pharmacological Engagement of Bcl-2 Proteins

We report the development of a new technology for monitoring multidimensional protein-protein interactions (PPIs) inside live mammalian cells using split RNA polymerase (RNAP) tags. In this new system, a protein-of-interest is tagged with an N-terminal split RNAP (RNAPN), and multiple potential binding partners are each fused to orthogonal C-terminal RNAPs (RNAPC). Assembly of RNAPN with each RNAPC is highly dependent on interactions between the tagged proteins. Each PPI-mediated RNAPN-RNAPC assembly transcribes from a separate promoter on a supplied DNA substrate, thereby generating a unique RNA output signal for each PPI. We develop and validate this new approach in the context of the Bcl-2 family of proteins. These key regulators of apoptosis are important cancer mediators, but are challenging to therapeutically target due to imperfect selectivity that leads to either off-target toxicity or tumor resistance. We demonstrate binary (1 × 1) and ternary (1 × 2) Bcl-2 PPI analyses by imaging fluorescent protein translation from mRNA outputs. Next, we perform a 1 × 4 PPI network analysis by direct measurement of four unique RNA signals via RT-qPCR. Finally, we use these new tools to monitor pharmacological engagement of Bcl-2 protein inhibitors, and uncover inhibitor-dependent competitive PPIs. The split RNAP tags improve upon other protein fragment complementation (PFC) approaches by offering both multidimensionality and sensitive detection using nucleic acid amplification and analysis techniques. Furthermore, this technology opens new opportunities for synthetic biology applications due to the versatility of RNA outputs for cellular engineering applications.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators.

A Panel of Protease-Responsive RNA Polymerases Respond to Biochemical Signals by Production of Defined RNA Outputs in Live Cells

RNA is an attractive biomolecule for biosensing and engineering applications due to its information storage capacity and ability to drive gene expression or knockdown. However, methods to link chemical signals to the production of specific RNAs are lacking. Here, we develop protease-responsive RNA polymerases (PRs) as a strategy to encode multiple specific proteolytic events in defined sequences of RNA in live mammalian cells. This work demonstrates that RNAP-based molecular recording devices can be deployed for multimodal analyses of biochemical activities or to trigger gene circuits using measured signaling events.

Transplantation of prokaryotic two-component signaling pathways into mammalian cells

Signaling pathway engineering is a promising route toward synthetic biological circuits. Histidine-aspartate phosphorelays are thought to have evolved in prokaryotes where they form the basis for two-component signaling. Tyrosine-serine-threonine phosphorelays, exemplified by MAP kinase cascades, are predominant in eukaryotes. Recently, a prokaryotic two-component pathway was implemented in a plant species to sense environmental trinitrotoluene. We reasoned that "transplantation" of two-component pathways into mammalian host could provide an orthogonal and diverse toolkit for a variety of signal processing tasks. Here we report that two-component pathways could be partially reconstituted in mammalian cell culture and used for programmable control of gene expression. To enable this reconstitution, coding sequences of histidine kinase (HK) and response regulator (RR) components were codon-optimized for human cells, whereas the RRs were fused with a transactivation domain. Responsive promoters were furnished by fusing DNA binding sites in front of a minimal promoter. We found that coexpression of HKs and their cognate RRs in cultured mammalian cells is necessary and sufficient to strongly induce gene expression even in the absence of pathways' chemical triggers in the medium. Both loss-of-function and constitutive mutants behaved as expected. We further used the two-component signaling pathways to implement two-input logical AND, NOR, and OR gene regulation. Thus, two-component systems can be applied in different capacities in mammalian cells and their components can be used for large-scale synthetic gene circuits.

Bacterial computing: a form of natural computing and its applications

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

The biological microprocessor, or how to build a computer with biological parts

Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system.

A formalized design process for bacterial consortia that perform logic computing

The concept of microbial consortia is of great attractiveness in synthetic biology. Despite of all its benefits, however, there are still problems remaining for large-scaled multicellular gene circuits, for example, how to reliably design and distribute the circuits in microbial consortia with limited number of well-behaved genetic modules and wiring quorum-sensing molecules. To manage such problem, here we propose a formalized design process: (i) determine the basic logic units (AND, OR and NOT gates) based on mathematical and biological considerations; (ii) establish rules to search and distribute simplest logic design; (iii) assemble assigned basic logic units in each logic operating cell; and (iv) fine-tune the circuiting interface between logic operators. We in silico analyzed gene circuits with inputs ranging from two to four, comparing our method with the pre-existing ones. Results showed that this formalized design process is more feasible concerning numbers of cells required. Furthermore, as a proof of principle, an Escherichia coli consortium that performs XOR function, a typical complex computing operation, was designed. The construction and characterization of logic operators is independent of “wiring” and provides predictive information for fine-tuning. This formalized design process provides guidance for the design of microbial consortia that perform distributed biological computation.