Frances H. Arnold

A Microfabricated Fluorescence-Activated Cell Sorter

We have demonstrated a disposable microfabricated fluorescence-activated cell sorter (μFACS) for sorting various biological entities. Compared with conventional FACS machines, the μFACS provides higher sensitivity, no cross-contamination, and lower cost. We have used μFACS chips to obtain substantial enrichment of micron-sized fluorescent bead populations of differing colors. Furthermore, we have separated Escherichia coli cells expressing green fluorescent protein from a background of nonfluorescent E. coli cells and shown that the bacteria are viable after extraction from the sorting device. These sorters can function as stand-alone devices or as components of an integrated microanalytical chip.

A synthetic multicellular system for programmed pattern formation.

Pattern formation is a hallmark of coordinated cell behaviour in both single and multicellular organisms. It typically involves cell–cell communication and intracellular signal processing. Here we show a synthetic multicellular system in which genetically engineered ‘receiver’ cells are programmed to form ring-like patterns of differentiation based on chemical gradients of an acyl-homoserine lactone (AHL) signal that is synthesized by ‘sender’ cells. In receiver cells, ‘band-detect’ gene networks respond to user-defined ranges of AHL concentrations. By fusing different fluorescent proteins as outputs of network variants, an initially undifferentiated ‘lawn’ of receivers is engineered to form a bullseye pattern around a sender colony. Other patterns, such as ellipses and clovers, are achieved by placing senders in different configurations. Experimental and theoretical analyses reveal which kinetic parameters most significantly affect ring development over time. Construction and study of such synthetic multicellular systems can improve our quantitative understanding of naturally occurring developmental processes and may foster applications in tissue engineering, biomaterial fabrication and biosensing.

Why highly expressed proteins evolve slowly

Much recent work has explored molecular and population-genetic constraints on the rate of protein sequence evolution. The best predictor of evolutionary rate is expression level, for reasons that have remained unexplained. Here, we hypothesize that selection to reduce the burden of protein misfolding will favor protein sequences with increased robustness to translational missense errors. Pressure for translational robustness increases with expression level and constrains sequence evolution. Using several sequenced yeast genomes, global expression and protein abundance data, and sets of paralogs traceable to an ancient whole-genome duplication in yeast, we rule out several confounding effects and show that expression level explains roughly half the variation in Saccharomyces cerevisiae protein evolutionary rates. We examine causes for expressions dominant role and find that genome-wide tests favor the translational robustness explanation over existing hypotheses that invoke constraints on function or translational efficiency. Our results suggest that proteins evolve at rates largely unrelated to their functions and can explain why highly expressed proteins evolve slowly across the tree of life.

Programmed population control by cell–cell communication and regulated killing

De novo engineering of gene circuits inside cells is extremely difficult, and efforts to realize predictable and robust performance must deal with noise in gene expression and variation in phenotypes between cells. Here we demonstrate that by coupling gene expression to cell survival and death using cell–cell communication, we can programme the dynamics of a population despite variability in the behaviour of individual cells. Specifically, we have built and characterized a ‘population control’ circuit that autonomously regulates the density of an Escherichia coli population. The cell density is broadcasted and detected by elements from a bacterial quorum-sensing system, which in turn regulate the death rate. As predicted by a simple mathematical model, the circuit can set a stable steady state in terms of cell density and gene expression that is easily tunable by varying the stability of the cell–cell communication signal. This circuit incorporates a mechanism for programmed death in response to changes in the environment, and allows us to probe the design principles of its more complex natural counterparts.

Engineering microbial consortia: a new frontier in synthetic biology

Microbial consortia are ubiquitous in nature and are implicated in processes of great importance to humans, from environmental remediation and wastewater treatment to assistance in food digestion. Synthetic biologists are honing their ability to program the behavior of individual microbial populations, forcing the microbes to focus on specific applications, such as the production of drugs and fuels. Given that microbial consortia can perform even more complicated tasks and endure more changeable environments than monocultures can, they represent an important new frontier for synthetic biology. Here, we review recent efforts to engineer synthetic microbial consortia, and we suggest future applications.

Directed evolution of a genetic circuit

The construction of artificial networks of transcriptional control elements in living cells represents a new frontier for biological engineering. However, biological circuit engineers will have to confront their inability to predict the precise behavior of even the most simple synthetic networks, a serious shortcoming and challenge for the design and construction of more sophisticated genetic circuitry in the future. We propose a combined rational and evolutionary design strategy for constructing genetic regulatory circuits, an approach that allows the engineer to fine-tune the biochemical parameters of the networks experimentally in vivo. By applying directed evolution to genes comprising a simple genetic circuit, we demonstrate that a nonfunctional circuit containing improperly matched components can evolve rapidly into a functional one. In the process, we generated a library of genetic devices with a range of behaviors that can be used to construct more complex circuits.

Combinatorial and computational challenges for biocatalyst design.

Nature provides a fantastic array of catalysts extremely well suited to supporting life, but usually not so well suited for technology. Whether biocatalysis will have a significant technological impact depends on our finding robust routes for tailoring natures catalysts or redesigning them anew. Laboratory evolution methods are now used widely to fine-tune the selectivity and activity of enzymes. The current rapid development of these combinatorial methods promises solutions to more complex problems, including the creation of new biosynthetic pathways. Computational methods are also developing quickly. The marriage of these approaches will allow us to generate the efficient, effective catalysts needed by the pharmaceutical, food and chemicals industries and should open up new opportunities for producing energy and chemicals from renewable resources.

Laboratory evolution of peroxide-mediated cytochrome P450 hydroxylation

Enzyme-based chemical transformations typically proceed with high selectivity under mild conditions, and are becoming increasingly important in the pharmaceutical and chemical industries. Cytochrome P450 monooxygenases (P450s) constitute a large family of enzymes of particular interest in this regard. Their biological functions, such as detoxification of xenobiotics and steroidogenesis, are based on the ability to catalyse the insertion of oxygen into a wide variety of compounds. Such a catalytic transformation might find technological applications in areas ranging from gene therapy and environmental remediation to the selective synthesis of pharmaceuticals and chemicals. But relatively low turnover rates (particularly towards non-natural substrates), low stability and the need for electron-donating cofactors prohibit the practical use of P450s as isolated enzymes. Here we report the directed evolution of the P450 from Pseudomonas putida to create mutants that hydroxylate naphthalene in the absence of cofactors through the ‘peroxide shunt’ pathway, with more than 20-fold higher activity than the native enzyme. We are able to screen efficiently for improved mutants by coexpressing them with horseradish peroxidase, which converts the products of the P450 reaction into fluorescent compounds amenable to digital imaging screening. This system should allow us to select and develop mono- and di-oxygenases into practically useful biocatalysts for the hydroxylation of a wide range of aromatic compounds.

Laboratory evolution of a soluble, self-sufficient, highly active alkane hydroxylase

We have converted cytochrome P450 BM-3 from Bacillus megaterium (P450 BM-3), a medium-chain (C12–C18) fatty acid monooxygenase, into a highly efficient catalyst for the conversion of alkanes to alcohols. The evolved P450 BM-3 exhibits higher turnover rates than any reported biocatalyst for the selective oxidation of hydrocarbons of small to medium chain length (C3–C8). Unlike naturally occurring alkane hydroxylases, the best known of which are the large complexes of methane monooxygenase (MMO) and membrane-associated non-heme iron alkane monooxygenase (AlkB), the evolved enzyme is monomeric, soluble, and requires no additional proteins for catalysis. The evolved alkane hydroxylase was found to be even more active on fatty acids than wild-type BM-3, which was already one of the most efficient fatty acid monooxgenases known. A broad range of substrates including the gaseous alkane propane induces the low to high spin shift that activates the enzyme. This catalyst for alkane hydroxylation at room temperature opens new opportunities for clean, selective hydrocarbon activation for chemical synthesis and bioremediation.

Directed evolution of enzyme catalysts

Directed enzyme evolution has emerged in the past few years as a powerful alternative to rational approaches for engineering biocatalysts. Prerequisites for successful directed evolution are functional expression in a suitable microbial host, a rapid screen for the desired feature(s) and a well-thought-out working strategy for navigating protein landscapes. The rapidly growing body of literature on enzyme evolution in vitro includes techniques for creating and searching combinatorial enzyme libraries, as well as several successful examples of different evolutionary strategies being used.