Using DNA Microarrays to Assay Part Function

Abstract

In recent years, the capability of synthetic biology to design large genetic circuits has dramatically increased due to rapid advances in DNA synthesis technology and development of tools for large-scale assembly of DNA fragments. Large genetic circuits require more components (parts), especially regulators such as transcription factors, sigma factors, and viral RNA polymerases to provide increased regulatory capability, and also devices such as sensors, receivers, and signaling molecules. All these parts may have a potential impact upon the host that needs to be considered when designing and fabricating circuits. DNA microarrays are a well-established technique for global monitoring of gene expression and therefore are an ideal tool for systematically assessing the impact of expressing parts of genetic circuits in host cells. Knowledge of part impact on the host enables the user to design circuits from libraries of parts taking into account their potential impact and also to possibly modify the host to better tolerate stresses induced by the engineered circuit. In this chapter, we present the complete methodology of performing microarrays from choice of array platform, experimental design, preparing samples for array hybridization, and associated data analysis including preprocessing, normalization, clustering, identifying significantly differentially expressed genes, and interpreting the data based on known biology. With these methodologies, we also include lists of bioinformatic resources and tools for performing data analysis. The aim of this chapter is to provide the reader with the information necessary to be able to systematically catalog the impact of genetic parts on the host and also to optimize the operation of fully engineered genetic circuits.

Introduction

The focus of synthetic biology has been the design and implementation of small-scale genetic circuits (Elowitz and Leibler, 2000, Ham et al., 2008, Tabor et al., 2009), including the transplantation and reconstruction of small metabolic pathways in suitable hosts (Lee et al., 2008, Steen et al., 2010). The focus on small systems reflected, in part, the laborious processes of DNA fragment construction and assembly required to optimize designed systems. The rapid expansion of DNA synthesis capacity (Czar et al., 2009, Tian et al., 2009) and the development of simple protocols for large-scale assembly of DNA fragments (Gibson et al., 2008, Gibson et al., 2009) have broadened the potential focus of synthetic biology. However, larger synthetic circuits require more components (Voigt, 2006), and their reliable operation requires accurate assessments of the impact of each of these components on the host cell processes. When such circuits overburden the host, mutations will rapidly accumulate to relieve the stresses that are introduced. An accurate assessment of the impact of synthetic circuits on host physiology will enable intelligent choice of the circuits chosen for implementation.

The components of synthetic circuits and their impact on the host can be broadly classified into two categories: (1) Regulatory components comprised transcription factors, sigma factors, and viral RNA polymerases, which enable controlled expression of individual circuit components. Importantly, the DNA sequence specificities of the regulators may result in aberrant and possibly deleterious gene expression within the host. (2) Circuit devices comprised sensors, receivers, signaling molecules, enzymes, etc. These components receive information and then command the cell to perform a task, such as producing chemicals and fuels, secreting proteins, and sending out communication signals. Individual circuit components may be deleterious to the host when overexpressed. Additionally, certain combinations of components may be deleterious even when the individual components have no deleterious effect. Consequently, it is importantly to monitor and catalog the impact of individual and combinations of circuit components on the host in order to facilitate the design process, the choice of components for a particular circuit, and troubleshooting of large synthetic circuits. In addition, a good understanding of the impact of components may facilitate modification of the host to better tolerate the circuit. For example, high level expression of some proteins can result in the accumulation of unfolded products within the cytoplasm, triggering the cytoplasmic heat shock response. This can be relieved by overexpression of cytosolic chaperones.

DNA microarrays provide an easy way to monitor changes in gene expression in the host (Rhodius et al., 2002). They can be used to pinpoint the effects of regulator parts of genetic circuits and provide a useful tool for identifying stress-response pathways that are upregulated in response to circuit devices. In this chapter, we will describe the process of performing microarray experiments and associated data analysis to monitor gene expression. The overall process is illustrated in Fig. 4.1 and involves the following steps: (1) Experimental setup: the biological question addressed, experimental design, and performing the microarray experiment(s); (2) Preprocessing: data quality control and normalization prior to analysis; and (3) Analysis: the statistical tools that identify significantly differentially expressed genes, clustering to identify coregulated genes or similar datasets, and functional annotation to identify common and/or enriched properties of the gene products in the final datasets. We discuss each step and indicate the utility of this technology for synthetic biology.