Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism.
Gene clusters are the genetic building blocks of bacteria and archaea. Prokaryotic genomes are highly organized and the genes associated with a particular function often occur near each other (Fischbach et al., 2008). Occasionally, all of the genes that are necessary for a discrete function form a cluster in the genome. These clusters encode functions that affect all aspects of the life style of bacteria, including nutrient scavenging, energy production, chemical synthesis, and environmental sensing. Large protein scaffolds, nanomachines, and cytoplasmic organelles are also encoded within clusters. These functions could play a central role for many applications in biotechnology; however, their complexity makes them difficult to engineer. Here, we survey the wide range of cellular functions that are known to be encoded in these genetically compact units with an eye on their potential ability to be transferable modules in multiple host species for engineering applications.
The organization of genes into clusters may facilitate the transfer of complete functions during evolution (Fischbach et al., 2008; Lawrence and Roth, 1996). All of the gene clusters presented in this review have some evidence for horizontal transfer, including phylogenetic trees disparate from ribosomal RNA, differing G+C content, and the presence of flanking transposon/integron genes (Ochman et al., 2000; Karlin, 2001). Phage genomes and conjugative plasmids also contain bacterial gene clusters, implying that a mobile element can confer a fitness advantage on its host by adding a novel function. For example, the photosynthetic apparatus (Lindell et al., 2004) and type IV pili (Karaolis et al., 1999) have been observed in phage genomes. Because gene clusters appeared and were shaped by interspecies transfer, it is intriguing that they could be fodder for genome building, where they provide a convenient unit of DNA that could be utilized to introduce a novel function into a synthetic organism. To date, such transfers are sometimes successful and sometimes fail for unknown reasons (Dixon and Postgate, 1972; Hansen-Wester et al., 2004). Potential problems include that the cluster may rely on regulatory interactions that are not present in the new host, the genes do not express or express at the wrong ratios, or there are auxiliary interactions with, or dependencies on, the host (Fischbach et al., 2008).
Within gene clusters, there can also be sub-gene clusters that evolve separately. This modular organization of clusters within clusters enables rapid diversification and can replicate a useful function in multiple contexts. Two examples of such sub-clusters are microcompartments that can sequester toxic metabolic intermediates (Section 2.2) and the stressosome that can integrate signals and control different signaling mechanisms (Section 6.1). Sub-clusters also occur within metabolic pathways, where particular conversion (e.g., the modification of a sugar moiety) can occur in different contexts. Examples of such sub-clusters are present in the erythromycin pathway (Section 4.3). The useful functions encoded by these sub-clusters have propagated into different metabolic and signaling pathways.
As the number of complete sequenced genomes grows, it has become clear that many gene clusters are “cryptic;” in other words, there are no known conditions under which the genes are expressed (Challis, 2008). Homology analysis can be useful (albeit inexact) in predicting the general classes of molecules produces. For example, there may be many novel antibiotics and other pharmaceuticals that are encoded by such clusters. Sometimes, it is possible to “wake up” a cluster by engineering its regulatory circuitry (Scherlach and Hertweck, 2009). This could either be through the deletion of a repressor or the addition of an inducible system. However, many clusters remain intransigent to these approaches. As the sequence databases grow, it is going to be increasingly tempting to access the functions encoded therein.
Genetic engineering is moving towards the era of the genome. Automated DNA synthesis has continued to advance, with the size of routine orders increasing to >50 000 bp, and declining cost and turnaround time (Czar et al., 2008). Recently, the entire wild-type genome of Mycoplasma was synthesized and transferred into a new cell, producing a living organism (Gibson et al., 2010). However, no design was implemented in this tour-de-force project; essentially, a natural genome was replicated. In an attempt to improve our design capacity, synthetic biology has been contributing a growing toolbox of genetic parts (e.g., ribosome binding sites, promoters, terminators) and devices (e.g., genetic circuits, sensors) that enable programmable control over transcription and translation (Voigt, 2006). In addition, methods have been developed to rapidly assemble these parts into intermediate 10-kb fragments (Gibson et al., 2009), which can then be further assembled to multi-100-kb pieces (Benders et al., 2010).
As synthetic biology moves towards genome design, gene clusters are an appropriate intermediate stepping stone. On one hand, they are themselves composed of genetic parts and devices. On the other, they could be hierarchically combined to add functions to a genome. Indeed, this type of construction occurs frequently in nature, where large plasmids have been discovered that contain multiple gene clusters (e.g., the pRSB107 plasmid combines nine antibiotic resistance gene clusters and one that scavenges iron) (Szczepanowski et al., 2005).
This review is organized to describe and compare clusters that encode a variety of functions from different species. The clusters are loosely organized into five classes according to the type of function they encode: structural, scavenging, synthesis, energy, and sensing. Each example focuses on a well-studied instance of that cluster. Many variations of each cluster exist. We also describe the current and potential applications in biotechnology for each of the gene clusters.
2. Nano-Machines, Organelles, and Large Protein Structures
2.1. Molecular Hypodermic Needle: Type III Secretion System Salmonella typhimurium (sprB to invH)
The type III secretion system (T3SS) is a molecular machine that exports proteins from the cytoplasm to the extracellular environment (Fig. A21-1) (Cornelis, 2006). Many Gram-negative pathogens have such systems, where it forms a syringe-like structure (Schraidt et al., 2010) that injects proteins into animal or plant cells to hijack a variety of host processes. The length of the needle varies depending on the function, from 60 nm in Yersinia to 2 μm in Pseudomonas syringae, where it needs to penetrate a thick plant cell wall. Effector proteins that are exported have an N-terminal secretion tag and a chaperone-binding domain that direct it to the needle. The proteins are actively unfolded before being transported through a 2-nm pore. All of the genes that are required to form the needle, as well as chaperones and effectors, are encoded within a single gene cluster (Fig. A21-2). Additional effector proteins can be scattered throughout the genome. A complex regulatory network encoded within the cluster integrates environmental signals and controls the dynamics of gene expression (Temme et al., 2008). Pathogens often have multiple clusters encoding needles that are responsible for different phases of an infection. The flagellum, involved in propulsion when bacteria swim, is a distantly related T3SS, but its genes are usually not organized into a single cluster.
Salmonella and other pathogenic bacteria have been explored for therapeutic uses as a mechanism to deliver vaccines and to block the growth of tumors. As a live vaccine, Salmonella has been used to deliver heterologous antigens from diverse sources to the immune system, including through the integration of peptides into effectors that are secreted from the T3SS encoded in Salmonella pathogenicity island 1 (SPI-1) (Galen et al., 2009). Salmonella naturally localizes to tumors after infection and it has been explored as an anticancer therapeutic, and has gone through clinical trials. The growth suppression of tumors has been shown to be dependent on the T3SS encoded within Salmonella pathogenicity island 2 (SPI-2) (Pawelek et al., 2002).
2.2. Chemical Reactors Within Bacteria: Microcompartments Salmonella typhimurium (pduA to pduX)
Many bacteria build geometrically regular polyhedral organelles with a diameter of 80–200 nm (Fig. A21-1) (Yeats et al., 2010; Kerfeld et al., 2010). These act as microcompartments to encapsulate enzymes that participate in metabolic pathways where an intermediate is toxic or requires concentration. The canonical example is the carboxysome, which co-localizes carbonic anydrase, which increases the concentration of CO2 with the CO2-fixing enzyme RuBisCo. There are several examples where a pathway produces an intermediate molecule that causes toxicity when it is produced in the cytoplasm. Examples include pathways for the utilization of propanediol and ethanolamine, whose toxic intermediates are aldehyde and acetaldehyde, respectively. An example of the former is the pdu gene cluster in Salmonella typhimurium. The proteins that form the microcompartments produce a sixfold symmetry with a 2–3-Å pore that can potentially expand to 11–13 Å. The pore controls the transport of molecules in and out of the microcompartment and has a variable amino acid sequence. The core structural components of the microcompartment are conserved and appear in gene clusters with the enzymes that make up the metabolic pathway (Fig. A21-2). For example the ethanolamine utilization gene cluster has 17 genes, 4 of which are the compartment shell proteins.
Microcompartments exist in natural pathways to solve many of the problems that emerge in metabolic engineering. Frequently, an intermediate metabolite is toxic and this is detrimental to the cell if the flux in and out are unbalanced, causing the intermediate to accumulate (Mukhopadhyay et al., 2008). Further, some enzymes have an intrinsically high Km, requiring that the substrate be concentrated. Other functions require an anaerobic environment, and it has been shown that microcompartments can exclude oxygen molecules. Effectively harnessing microcompartments will require that targeting sequences be available to direct enzymes to the organelle (Fan et al., 2010) and protein engineering methods to alter the pores to allow desired substrates to enter (Yeats et al., 2010). Several microcompartments have been predicted to be involved in pathways of direct relevance to biotechnology, including in the production of ethanol in Vibrio (Wackett et al., 2007) and butyrate in Clostridium (Seedorf et al., 2008).
2.3. Balloons in Bacteria: Gas Vesicles Halobacterium salinarum (gvpA to gvpM)
A variety of species of archaea and bacteria control their buoyancy by forming gas-filled balloons in their cytoplasm (Fig. A21-1) (Pfeifer, 2006; Walsby, 1994). They function to maintain a desired depth in an aquatic environment, and their inflation and deflation are regulated by environmental signals that are used to identify the correct depth, including UV, light intensity, salinity, and oxygen. To have an effect on buoyancy, at least 10% of the cell volume needs to be composed of gas vesicles; thus, some bacteria have >10 000 per cell depending on their size. These vesicles are large, ranging in size from 33 to 250 nm in diameter, but they have very thin walls—about 2 nm—made entirely of protein. The protein that is the major component of the wall is GpvA, which forms a hydrophobic inner surface that blocks the formation of water droplets via surface tension. Gas enters the vesicles via diffusion and it is not stored there, rather it is in equilibrium with the surrounding concentration of dissolved gas (Walsby, 1994). The filling time is 0.4 μs. The vesicles can be filled by small and large gas molecules, including O2, N2, H2, CO2, CO, CH4, Ar, and C4F8. All of the genes necessary for gas vesicle formation occur together in a gene cluster, including the core structural proteins, accessory proteins that control the size and shape, chaperones, seeding proteins, and regulators (Fig. A21-2). Vesicles are produced when the gene cluster from Bacillus megaterium is transferred into Escherichia coli (Li and Cannon, 1998).
Recombinant proteins can be inserted to an accessory protein (GvpC) that participates in the formation of the shell of the gas vesicle. Antibodies have been produced and purified in this way, where the buoyancy of the vesicle aids purification and delivery (Sremac and Stuart, 2008). Gas vesicles isolated from cyanobacteria have been shown to improve oxygen transport in a mammalian cell fermentation (Sundararajan and Ju, 2000). Very interestingly, vesicles have been discovered in terrestrial bacteria that have been studied for their diverse secondary metabolisms, including antibiotic production (such as Streptomyces avermitilis), although their role in these organisms has yet to be determined (van Keulen et al., 2005). Perhaps the most interesting aspect of blowing up balloons in bacteria is that it is fun (Endy et al., 2005).
2.4. Metal Nanoparticles: Magnetosomes Magnetospirillum magneticum AMB-1 (mamC to mamF)
Biomineralization is a process by which bacteria build intricate 3-D nano-structures from dissolved metal. One of the most dramatic structures is the magnetosome, which is used by bacteria that can orient their swimming to align with the geomagnetic field (magnetotaxis) (Fig. A21-1) (Jogler and Schuler, 2009). Spherical nanocrystals (diameter ~30–50 nm) of iron oxide magnetite (Fe3O4) are contained within lipid organelles (Komeili, 2007). A string of these crystals are held in a chain orientation by proteins that resemble those involved in the cytoskeleton. All of the genes that encode the proteins involved in the biosynthesis, organization, and regulation of the magnetosome are encoded in a conserved Magnetosome Island (MAI) region of the genome that spans 80–150 kb (Fig. A21-2). This region has been noted to be unstable, and is frequently lost in lab culture. MAIs are phylogenetically widespread and there is diversity in the size, shape, and mineral composition of the crystals (Komeili, 2007).
The process by which magnetosome crystals are grown produces remarkably uniform and highly ordered structures (Jogler and Schuler, 2009). The bacteria also have the ability to concentrate low environmental abundances of metals and form crystals under mild conditions compared to chemical routes (Schuler and Frankel, 1999). Further, their synthesis in a lipid membrane makes them easily dispersed in an aqueous environment. Thus, magnetosome-producing cells have the potential to be harnessed for the industrial production of magnetic nanoparticles, with diverse applications in medicine, imaging, and commercial uses in magnetic tape and ink (Schuler and Frankel, 1999; Matsunaga et al., 2007). Beyond Fe-based magnetosomes, many bacteria are able to build structures of diverse size (1–6000 nm), complexity (spherical, triangular, octahedral, decahedral, cubic, plates), and out of a variety of materials (gold, silver, cadmium, palladium, selenium, titanium, lanthanum, zinc, uranium, lead) (Korbekandi et al., 2009).
3. Scavenging for Nutrients
3.1. Molecular Chainsaws: The Cellulosome Clostridium cellulolyticum (cipC to cel5N)
Cellulose is a polymer of sugar molecules and is an abundant component of plant cell walls. It is the most abundant polymer in biomass and many organisms have the ability to degrade this material to obtain carbon and energy. They do this by secreting cellulases and other enzymes that are able to break down complex cell walls to release simpler sugars that can diffuse into the cell. In clostridia and rumen organisms, these enzymes frequently cluster to form a large cellulosome that protrudes from the cell surface (Fig. A21-1) (Fontes and Gilbert, 2010).
The cellulosome consists of a scaffolding protein (scaffoldin) that contains a series of cohesin domains. These domains bind to dockarin domains at the N termini of the cellulases that are involved in the assembly of the cellulosome. The scaffoldin is tethered to the cell surface (often to the S layer) and it and many of the cellulases contain cellulose-binding domains so that they bind to the cellulose in the plant cell wall (Desvaux, 2005). The advantage of having a cellulosome has been postulated to be that there is a higher likelihood that the released sugars will be consumed by the organism (Fontes and Gilbert, 2010). There is much diversity in the size and composition of cellulosomes and additional enzyme activities are commonly present, including hemicellulases and pectins to aid the decomposition of the plant cell wall. The cellulosomes can be very large, with up to 200 enzymes, and can be up to 16 MDa (Desvaux, 2005; Ding et al., 2001). Within species, the cohesin-dockarin interactions are not specific and individual enzymes are not discriminated at each position in the scaffoldin. Remarkably, the enzyme composition of the cellulosome reflects the substrate on which the cells were grown; for example, on grass clippings, pectins are expressed, and on sewage soils consisting of insect biomass, chitinases are expressed (Desvaux, 2005). The genetic regulation that controls this adaptation is unknown.
The scaffolding protein and many of the enzymes are often organized into a gene cluster (Fig. A21-2). The cluster in C. cellolyticum is a model system with 12 genes encoded in a 26-kb region, and the pattern of phylogenetic distribution implies horizontal transfer (Desvaux, 2005). CipC is the scaffoldin and there are 8 cellulases, 1 hemicellulase (Man5K), and 1 pectinase (Cc-Rgl11Y) present in the cluster. The breakdown of crystalline cellulose is complex and requires synergistic activities between multiple enzymes. Some enzymes cut the polymer at random locations (exoglucanase), whereas others start from either free reducing or non-reducing ends and progressively cleave the polymer (endoglucanase). The most prevalent enzymes of this cellulosome represent one from each category: Cell9E and Cell48F (Desvaux, 2005). Cell9E randomly cuts the cellulose strands. In contrast, Cell48F forms a long hydrophobic tunnel, through which cellulose strands are threaded as it progressively cuts and releases simpler sugars. C. cellulolyticum contains 62 enzymes that contain dockarin domains and the enzyme composition has been shown to vary based on the substrate on which bacteria grow (Blouzard et al., 2010).
Biofuels and renewable chemicals require a source of carbon. Currently, this is frequently obtained in the form of sugar from crops such as corn and sugarcane. Particularly for fuels, this poses sustainability problems as agricultural crops would be diverted from food. In contrast, the amount of carbon that could be extracted from biomass is on the same scale as the fuels industry (and microbes have been estimated to naturally release the equivalent of 640 billion barrels of crude per year!) (Fontes and Gilbert, 2010). The problem is in the efficient liberation of carbon from cellulosic feedstocks, and this is currently a very active area of research. Significant effort has been put into the engineering of the cellulosome for this purpose (Bayer et al., 1994). One approach is to metabolically engineer natural cellulosic microbes to produce valuable products. A problem with this approach is that organisms containing cellulosomes are often not adapted for high carbon fluxes (Desvaux, 2005). A variety of metabolic engineering approaches have been used to increase the catabolism of these organisms. Another approach is to move the cellulosome into a noncellulolytic organism. This has been achieved for moving a minimal cellulosome to C. acetobutylicum (Sabathe and Soucaille, 2003) and the yeast S. cerevisiae (Lilly et al., 2009). Finally, the adhesin-dockarin domains have been harnessed as modules that control protein-protein interactions for a variety of applications outside of bioenergy, including protein purification and display (Nordon et al., 2009).
3.2. Eating Oil: Alkane Degradation Pathways Pseudomonas putida GPO1 (alkB to alkS)
Numerous marine and terrestrial bacteria have the ability to utilize hydrocarbons as a carbon and energy source (van Hamme et al., 2003). When oil leaks into seawater, this leads to the growth of a bloom of bacteria that are obligate consumers of alkanes (Yakimov et al., 2007). Many of the genes involved in the utilization of hydrocarbons occur together in a gene cluster (van Beilen et al., 2001). Petroleum is a chemically diverse substance and there are a range of enzymes and related pathways that break down different classes of molecules (van Beilen et al., 2001; van Beilen and Funhoff, 2007). The gene cluster in P. putida is one of the most well-studied systems and is able to degrade medium-length alkanes (Fig. A21-2) (van Beilen et al., 2001). The metabolic pathway begins with an alkane hydroxylase (AlkB—a membrane-associated non-heme diiron monooxygenase), which converts the alkane to an alcohol (Fig. A21-3) (van Beilen and Funhoff, 2007). Often, strains contain multiple alkane hydroxylases to broaden the range of substrates that can be consumed (van Hamme et al., 2003). Electrons are delivered to AlkB by two rubredoxins (AlkF and AlkG). The alcohol is converted to acyl-CoA in three steps (AlkHJK), at which point it can enter metabolism. Two additional proteins, AlkL and AlkN, putatively encode an importer and chemotaxis sensory protein, respectively. AlkS acts as an alkane sensor and up-regulates gene expression. The alk gene cluster occurs in many phylogenetically distinct bacteria (van Hamme et al., 2003). It has a lower G+C content than the genome and is flanked by transposon genes, which indicate frequent horizontal transfer.
Petroleum-degrading organisms have been proposed to be used in a wide variety of industrial applications. This includes a variety of potential roles in environmental cleanup, from biosensing and site evaluation to environmental dispersal, fermenter-based waste treatment, refinery waste treatment, and tanker ballast cleaning (van Hamme et al., 2003). Organisms and related pathways have been identified that can break down nearly all of the components of petroleum, including benzene, ethylbenzene, trimethylbenzene, toluene, ethyltoluene, xylene, naphthalene, methylnapthalene, phenanthrene, C6–C8 alkanes, C14–C20 alkanes, branched alkanes, and cymene (van Hamme et al., 2003). In addition, alkane-degrading organisms could be used as biocatalysts to add value to petroleum products (van Hamme et al., 2003). For example, Alcanivorax has been engineered to direct the carbon flux from alkanes to the production and export of the bioplastic precursor poly(hydroxyalkanoate) (PHA) (Sabirova et al., 2006). A particularly interesting use is for microbial enhanced oil recovery (MEOR), where bacteria are introduced into oil wells to facilitate secondary recovery (van Hamme et al., 2003). The injection of oil-degrading organisms can increase recovery by reducing viscosity or secreting surfactants. MEOR has been tested worldwide, including in the USA, and has led to increases of 15–23% for oil wells in Japan and China (van Hamme et al., 2003). Finally, the alkane-sensing transcription factor (AlkS) and the AlkB promoter have been transferred into E. coli to construct a genetic biosensor (Sticher et al., 1997).
3.3. Fertilizer Factories: Nitrogen Fixation Klebsiella pneumoniae (nifJ to nifQ)
The availability of nitrogen limits the growth of many organisms (Igarashi and Seefeldt, 2003). In agriculture, fixed nitrogen is a critical component of fertilizer and its availability has been linked to the growth of the human population. The primary source of nitrogen is from the atmosphere in the form of N2. Converting this into a form that can enter metabolism—such as ammonia (NH3)—is a difficult chemical reaction. The Haber-Bosch process can chemically convert N2 to NH3 using high temperatures and pressures using an iron catalyst. In contrast, biological nitrogen fixation uses a complex enzyme (nitrogenase) to perform this reaction (Fig. A21-3). Remarkably, the current flux of fixed nitrogen from synthetic chemical and natural biological processes is about equal (Igarashi and Seefeldt, 2003).
Only prokaryotes and some archaea have the ability to fix nitrogen (Dixon and Kahn, 2004). Often, all of the genes necessary for nitrogen fixation are encoded in a gene cluster. One of the simplest and most well-studied clusters is from K. pneumoniae, which consists of 20 genes encoded in 23 kb (Fig. A21-2) (Rubio and Ludden, 2008). These genes encode all of the necessary components for nitrogen fixation, including the nitrogenase, a metabolic pathway for the synthesis of metal co-factors, e− transport, and a regulatory network. Nitrogenase consists of two core proteins (NifH and the NifDK complex) that participate in a reaction cycle (Igarashi and Seefeldt, 2003). The reaction itself is very energy and redox intensive with the balance
Each reaction cycle consists of the transfer of 1 e− and the consumption of 2 ATP (the energy of which is used to greatly accelerate e− transfer). It is marked by a transient interaction between NifH, which receives an e− from a variety of sources, and NifDK, which contains the reaction center where N2 binds and fixation occurs. The cycle of binding, electron transfer, and dissociation needs to be repeated eight times to fix a single N2 molecule. Nitrogenase is slow (kcat = 5 s−1) and is thought to be limited by the dissociation step (Igarashi and Seefeldt, 2003). Three co-factors form the core of the e− transfer and catalysis: [Fe4-S4] in NifH, the P cluster [Fe8-S7] in NifDK, and FeMo-co [Mo-Fe7-S9-X] (Fig. A21-4) where the reaction occurs (Rubio and Ludden, 2008). The enzymes involved in the synthesis of these co-factors and chaperones for their incorporation to form mature nitrogenase make up the majority of the cluster (Fig. A21-3). It has been proposed that these proteins all form a macromolecular “biosynthetic factory” centered on the NifEN proteins (Rubio and Ludden, 2005). NifF and NifJ are a flavodoxins that feed electrons to NifH, with pyruvate as one source (Rubio and Ludden, 2005). Nitrogenase is extremely oxygen sensitive and expensive for the cells to make and run (Fischer, 1994). A simple regulatory cascade is formed by the activator NifA and the anti-activator NifL, which integrate signals to ensure that the genes are only expressed in the absence of oxygen and fixed nitrogen (Dixon and Kahn, 2004). Since the earliest tools in genetic engineering were developed, it has been a dream of biotechnology to create cereal crops that can fix their own nitrogen. The complexity of the nitrogen fixation pathway and a lack of efficient tools for modifying non-model plants have hindered progress in this area (Dixon et al., 1997). In contrast, the complete gene cluster was functionally transferred from Klebsiella to E. coli relatively early in 1972 (Dixon and Postgate, 1972). The chloroplast may be a potentially good target for the maturation and function of nitrogenase because: (1) it is where ammonia assimilation occurs, (2) ATP is generated there, (3) there is evidence that the ancillary proteins for Fe-S formation exist, and (4) the genetic context is similar to a prokaryote, including the ability to transcribe operons (Cheng, 2008). Individual genes from the pathway have been transferred to the Tobacco genome with a chloroplast-targeting peptide and to the plastid in the algae Chlamydomonas reinhardtii (Dixon et al., 1997). Neither of these efforts yielded appreciable expression. Besides the difficulty of expressing Klebsiella-encoded genes in these contexts, there are regulatory issues around the oxygen sensitivity of nitrogenase and, thus, its inconsistency with the photosynthetic processes in the chloroplast. One way to overcome this would be to place the nitrogenase under the control of light or oxygen sensitive transcription factors (Dixon et al., 1997), or to express oxygen-protective factors, including the “Shethna” protein from Azotobacter vinelandii (Moshiri et al., 1994) and some nitrogenases are intrinsically less sensitive to oxygen (Cheng, 2008). Several applications of nitrogenase have been proposed that do not involve as a cheap source of moving the system into a plant, including for the use of N2 nitrogen during fermentation (Chen et al., 2001), cyanide detoxification (Gupta et al., 2010), and the use of bacteria as biofertilizer (Bhattacharjee et al., 2008), and for the industrial production of ammonia (Brouers and Hall, 1986).
3.4. Bioremediation: Polychlorinated Biphenyl Degradation Burkholderia xenovorans LB400 (orf0 to bphD)
Some bacteria can use harmful organic pollutants as their sole source of carbon and energy (Pieper, 2005). For example, Burkholderia xenovorans LB400 can subsist on polychlorinated biphenyls (PCBs), which are used industrially as, among others, fire retardants and plasticizers (Fig. A21-4) (Pieper and Seeger, 2008). This capability has made B. xenovorans and other PCB-metabolizing bacteria key elements of bioremediation strategies for chemical spills. Highly chlorinated PCBs are reductively dehalogenated by organisms such as Dehalococcoides, which can use PCBs as a terminal electron acceptor for anaerobic respiration (Pieper and Seeger, 2008). These lower chlorinated PCBs are the substrate for the B. xenovorans degradation pathway, which consists of a series of enzyme-mediated oxidations culminating in the cleavage of one of the linked aromatic rings by the ring-opening dioxygenase BphC. The cleaved ring is converted to two equivalents of acetate in a three-step pathway, while the uncleaved ring is released as benzoic acid and then further processed to catechol by the protein products of the benABCD gene cluster (Fig. A21-2) (Pieper and Seeger, 2008).
Several strategies are being employed to increase the number of PCBs that can be degraded microbially, including directed evolution of a ring-cleaving dioxygenase (Fortin et al., 2005) and functional screening of metagenomic libraries from activated sludge (Suenaga et al., 2007). Future efforts may attempt to introduce PCB degradation gene clusters into bacterial strains that synthesize compounds of industrial value, which would allow these strains to consume feed-stocks that would otherwise require expensive and environmentally unfriendly disposal.
4. Biosynthesis of Chemicals
4.1. Bioplastic Biosynthesis: Poly(3-hydroxybutryrate) Ralstonia eutropha H16 (phbA to phbC)
Many bacteria synthesize poly(3-hydroxybutyrate) (PHB) and other PHAs as a means of storing carbon and energy intracellularly (Fig. A21-4). The biosynthetic pathway for PHB, exemplified by the phb gene cluster in Ralstonia eutropha (Fig. A21-2) (Pohlmann et al., 2006), consists of three steps: PhbA catalyzes a Claisen condensation to convert two molecules of acetyl-CoA to acetoacetyl-CoA, PhbB reduces acetoacetyl-CoA to 3-hydroxybutryl-CoA, and PhbC polymerizes 3-hydroxybutryl-CoA with release of CoA to form PHB (Madison and Huisman, 1999). PHB is hydrophobic and accumulates in cytoplasmic granules.
PHB and other PHAs are versatile bioplastics; biodegradable forms of a diverse set of products ranging from plastic bottles to golf tees are produced commercially from bacterially synthesized PHAs (Madison and Huisman, 1999). Efforts to metabolically engineer the synthesis of bioplastics are proceeding along two tracks. First, the genes for the production of PHB and other PHAs have been introduced into plants to realize the benefits of using CO2 as a carbon source rather than fermentation feedstocks (Slater et al., 1999). However, these efforts have been only modestly successful; to date, the best PHA production titer seen in plants is only ~10% of dry weight. Second, a variety of engineering efforts including genetic engineering and the provision of unnatural substrate derivatives in the fermentation broth have led to the optimization of PHA yields in native and engineered hosts and the production of novel PHA derivatives (Aldor and Keasling, 2003).
4.2. Nonribosomal Peptide Biosynthesis: Echinomycin Streptomyces lasaliensis (ecm1 to ecm18)
Nonribosomal peptides (NRPs) are a class of peptidic small molecules that includes the antibiotic vancomycin and the immunosuppressant cyclosporine (Fischbach and Walsh, 2006). The gene cluster for echinomycin (Fig. A21-4), a DNA-damaging NRP from the quinoxaline class, is typical in encoding four categories of gene products (Fig. A21-2): (1) Genes for miniature, self-contained metabolic pathways that provide unusual monomers. Eight ecm-encoded enzymes convert tryptophan into quinoxaline-2-carboxylic acid (QC), an unusual monomer that enables echinomycin to intercalate between DNA base pairs; (2) Genes for an assembly-line-like enzyme known as an NRP synthetase (NRPs) that link monomers (typically amino acids) into a peptide and then release it from covalent linkage to the assembly line, often with concomitant macrocyclization. The ecm gene cluster encodes two NRPS enzymes, Ecm6 (2608 amino acids) and Ecm7 (3135 amino acids), that convert QC, serine, alanine, cysteine, and valine into a cyclic, dimeric decapeptidolactone; (3) Genes for chemical ‘tailoring’ after release from the NRPS. Two ecm-encoded enzymes oxidatively fuse the two cysteine side chains into a thioacetal; and (4) Genes that encode regulatory and resistance functions. Transporters are also commonly found in NRP gene clusters (Gorby et al., 2006).
There are two ways in which synthetic biology is being used in the area of NRPS engineering. First, efforts are being made to express NRPS gene clusters in heterologous hosts, either in their native form (Penn et al., 2006) or re-engineered for E. coli (Gorby et al., 2006). Expression in a heterologous host can serve three purposes: making the encoded NRP accessible for structure elucidation or biological characterization, particularly useful if the native host is unknown or unculturable; making the genes easier to manipulate, which is useful if the native host is not amenable to genetics; and improving the production titer of its small molecule product, which is helpful if the gene cluster is repressed by an external regulatory system in the native host. Second, the production of NRP derivatives has been engineered by replacing portions of NRPs genes with variants from other gene clusters that lead to the incorporation of alternative amino acid building blocks. This technique has been used most extensively to generate derivatives of the NRP antibiotic daptomycin (Baltz, 2009).
4.3. Polyketide Biosynthesis: Erythromycin Saccharopolyspora erythraea NRRL 2338 (SACE_0712 to eryCI)
Polyketides (PKs) are a class of acetate- and propionate-derived small molecules that includes the immunosuppressant FK506, the antibiotic tetracycline, the cholesterol-lowering agent lovastatin, and a number of rapamycin analogues made by genetic engineering are in clinical trials (Fischbach and Walsh, 2006). The biosynthetic pathways for PKs and fatty acids are similar in their chemical logic and use related enzymes: both involve the polymerization of acetate- or propionate-derived monomers by a series of Claisen condensations followed by reduction of the resulting β-ketothioester (Fischbach and Walsh 2006). The gene cluster for erythromycin (Fig. A21-4), an antibacterial PK from the macrolide class, encodes the following classes of gene products (Fig. A21-2):
- 3 large PK synthase (PKS) enzymes—DEBS 1 (3545 amino acids), DEBS 2 (3567 amino acids), and DEBS 3 (3171 amino acids)—that convert seven equivalents of the propionate-derived monomer methyl-malonyl-CoA into the intermediate 6-deoxyerythronolide B (6-DEB);
- 2 P450s that hydroxylate the nascent scaffold;
- 12 enzymes that synthesize the unusual sugars desosamine and my-carose from glucose and attach them to the nascent scaffold. Without these sugars, erythromycin does not have appreciable antibiotic activity; and
- an erythromycin resistance gene that modifies the 50S subunit of the ribosome to prevent erythromycin from binding (Staunton and Weissman, 2001).
Many PKSs have been expressed in heterologous hosts such as E. coli, including the PKSs for erythromycin and the anticancer agent epothilone (Fujii, 2009). Another notable heterologous host is a variant of the Streptomyces fradiae strain used for the industrial production of the antibiotic tylosin; having gone through many rounds of classical strain improvement, the metabolism of this strain is well suited to the production of PKs. A variant of the strain was created in which the tylosin gene cluster was replaced by the erythromycin PKS yielding a high titer of the non-native product (Rodriguez et al., 2003). The PKS genes have been mutated or replaced with variants from other gene clusters to generate PK derivatives (McDaniel et al., 1999), or to create custom PKSs that synthesize small PK fragments by assembling portions of several PKS genes (Menzella et al., 2005).
4.4. Terpenoid Biosynthesis: Lycopene Rhodobacter capsulatus (crtE to crtY)
Terpenoids are a class of molecules that include the anticancer agent taxol, the antibiotic pleuromutilin, and the carotenoid pigments. While terpenoids are more common among plants than bacteria (Walsh and Fischbach, 2010), carotenoids are produced by a range of bacteria. Lycopene and other carotenoids are generally used in one of two ways: to harvest light (either for energy or photo-protection) or as antioxidants (Fig. A21-4). As with other terpenoids, the first step in the biosynthetic pathway for lycopene is the CrtE-catalyzed polymerization of the C5 monomer isopentenyl pyrophosphate (IPP) or its Δ2 isomer dimethallyl pyrophosphate (DMAPP), in this case to the C20 polymer geranylgeranyl diphosphate (GGDP). CrtB then dimerizes two equivalents of GGDP in a tail-to-tail fashion, resulting in the formation of the linear C40 polymer phytoene. CrtI catalyzes four successive desaturations to yield lycopene. Alternative products such as beta-carotene are formed by the action of CrtY, which cyclizes the termini of the linear polymer (Umeno et al., 2005). All of the genes in this pathway occur together in a cluster (Fig. A21-2).
The colored nature of carotenoids has enabled their pathways to be engineered by genetic screens with colony color phenotypes. For example, a library of shuffled phytoene desaturases was screened in an E. coli strain harboring the crt gene cluster, resulting in the identification of desaturase clones that enabled the production of two lycopene variants, 3,4,3′,4′-tetradehydrolycopene and torulene (Schmidt-Dannert et al., 2000). Much synthetic biological work has been done by Keasling and coworkers on the production of plant terpenes (e.g., artemisinin) in the microbial hosts S. cerevisiae (Cogdell et al., 2006) and E. coli (Martin et al., 2003). This effort has involved two key challenges. First, since biosynthetic genes are not physically clustered in plant genomes, identifying the genes involved in terpenoid biosynthesis has been difficult, although the ongoing projects to sequence the genomes of hundreds of plants should enable bioinformatic efforts to identify biosynthetic genes. Second, the metabolism of S. cerevisiae and E. coli has been optimized for the production of terpenoids by increasing the flux of carbon toward IPP and DMAPP; in E. coli this was accomplished by supplementing the endogenous IPP biosynthetic pathway with the one from S. cerevisiae.
4.5. Oligosaccharide Biosynthesis: Xanthan Xanthomonas campestris pv. campestris (gumB to gumM)
Every year, 10 000–20 000 tons of xanthan are produced for use in foods (e.g., to control the crystallization of ice cream and to emulsify salad dressings) and in industry (e.g., to modulate the viscosity of explosives and laundry detergents) (Becker et al., 1998). Xanthan, an oligosaccharide produced by the plant pathogen Xanthomonas campestris, is composed of a cellulose backbone, on alternating sugars of which a mannose-β-1,4-glucuronate-β-1,2-mannose tri-saccharide is appended (Fig. A21-4). A portion of the terminal mannoses have pyruvate linked as a ketal to the 4′- and 6′-hydroxyls, and some of the internal mannoses are acetylated on the 6′-hydroxyl. Owing to the glucuronate units and pyruvoyl substituents, xanthan is an acidic polymer. Xanthan biosynthesis involves the action of five glycosyltransferases (GumDMHKI), and the growing chain is anchored on undecaprenyl pyrophosphate, similarly to peptidoglycan biosynthesis (Fig. A21-2). Three tailoring enzymes (GumFGL) add the aforementioned pyruvoyl and acetyl substitutents, and GumBCE are required for xanthan export (Becker et al., 1998).
Future efforts are likely to proceed along two tracks. First, while substrate to xanthan conversion rates of 60–70% have been achieved (Becker et al., 1998), X. campestris could be engineered to grow on cheaper feedstocks or to make the separation of the cells from the xanthan less costly; alternatively, the gum gene cluster could be moved to an alternative host. Second, changes to the structure of xanthan have important effects on its rheological properties. Efforts to use genetic engineering to alter the structure (and therefore the rheological properties) of xanthan—or of other microbial exopolysaccharides such as alginate or gellan (Sa-Correia et al., 2002)—have the potential to create new polymers, e.g., with altered viscosity and shear stability.
4.6. Indolocarbazole Biosynthesis: Staurosporine Streptomyces sp. TP-A0274 (staR to staMB)
Indolocarbazoles are natural products formed by the oxidative fusion of primary metabolic monomers (Walsh and Fischbach 2010). Staurosporine, an in-dolocarbazole, is a promiscuous, nanomolar inhibitor of serine/threonine protein kinases that binds in an ATP-competitive manner to these enzymes (Fig. A21-4) (Sanchez et al., 2006; Nakano and Omura, 2009). The staurosporine gene cluster encodes three categories of gene products (Fig. A21-2): (1) Four oxidoreductases (two P450s and two flavoenzymes) that catalyze a net 10-electron oxidation to fuse two molecules of tryptophan into the indolocarbazole aglycone (Howard-Jones and Walsh, 2006); (2) nine enzymes to synthesize and attach an unusual hexose to the indolocarbazole scaffold at the indole nitrogens; and (3) a transcriptional activator that regulates the expression of the gene cluster. Other naturally occurring indolocarbazoles differ in the oxidation state of the indolocarbazole scaffold, the derivatization of the indole ring by chlorination, and the sugar substituent appended to the indolocarbazole aglycone.
More than 50 unnatural indolocarbazole derivatives have been made by assembling artificial gene clusters in a non-native host (Salas and Mendez, 2009). These molecules harbor chemical modifications that would be difficult to introduce by semisynthetic derivatization of naturally occurring indolocarbazoles or by total synthesis. The majority of these efforts have used genes from the gene clusters for indolocarbazoles as the building blocks for the artificial gene clusters. Future efforts to explore the activities of completely unrelated enzymes (e.g., ring-opening dioxygenases) may enable the modification of portions of the indolocarbazole scaffold—such as the external six-membered rings—that would be difficult to access using synthetic organic chemistry or enzymes from indolocarbazole gene clusters.
5. Energy Generation and Transfer
5.1. Solar Powerpacks: Photosynthetic Light Harvesting Rhodobacter sphaeoroides (pufH to pufX—and puc genes)
Sunlight is converted into power by the light harvesting system of anaerobic photosynthetic bacteria (Fig. A21-1) (Jones, 2009). Light energy is captured by two light harvesting complexes (LH1 and LH2) and is funneled to a reaction center (RC) (Cogdell et al., 2006). The RC uses the energy to produce a transmembrane charge separation mediated by the reduction of a quinone. This ultimately causes a proton to move from the cytoplasm to periplasm, which powers the production of ATP via the protonmotive force. The R. sphaeroides membrane has spherical invaginations that increase the surface area and number of RCs. Each RC occupies a hole in a ring formed by LH1. LH2 also forms rings that surround the RC:LH1 complex in the membrane. The LH complexes use carotenoids and bacteriochlorophyll (Fig. A21-4) to absorb green and near-infrared light, respectively (Cogdell et al., 2006). The photosynthetic genes are frequently found in a single cluster in purple bacteria (Naylor et al., 1999; Alberti et al., 1995). In R. sphaeroides, the photosynthesis gene cluster is 40.7 kb long and contains all of the necessary genes for the formation of the RC/LH1 (puf genes), and LH2 (puc genes) (Fig. A21-2). Two biosynthetic pathways make up the bulk of the cluster, where bacteriochlorophyll is produced from heme in a 16-gene pathway (bch genes) and the carotenoid sphaeroidine is produced from isopentenyl pyrophosphate in a 7-gene pathway (crt genes). The gene cluster is regulated by oxygen concentration, as well as the light intensity and color (Cogdell et al., 2006).
The Rhodobacter light harvesting system has been a model system for studying photosynthesis. It is relatively simple, there is only one photosystem, and the organism is genetically tractable. This has enabled detailed quantum mechanical measurements to be made on light absorption and electron transfer (Cogdell et al., 2006), which may enable the design of next-generation “biologically inspired” photovoltaic cells. Going one step further, the light harvesting complex can be functionally reconstituted in vitro and this has led to the construction of various hybrid systems, where the electrons are shuttled to inorganic materials (Lu et al., 2007). A particularly interesting approach is the development of a self-assembled monolayer, where the RC is tethered to a metal (Pt, Hg or Au) surface by an organic molecule that ends with a quinone. Multi-layer films have been constructed and shown to efficiently capture electrons. Rhodobacter has also been harnessed for producing H2 from light for use in fuel cells or microbial fuel cells (Logan and Regan, 2006).
5.2. Nanowires: Conductive Surface Pili Geobacter sulfurreducens (pilB to pilA)
Metal-reducing bacteria are able to discharge electrons to solid surfaces through “wires” formed by pili that extrude from the cell surface (Fig. A21-1) (Reguera et al., 2005). This gives these bacteria the required terminal electron acceptor for oxidative phosphorylation in the absence of other dissolved acceptors (oxygen, nitrate, sulfate, etc) (El-Naggar et al., 2008). Geobacter is able to form pili that attach to Fe(III) oxide surfaces. The genes that form the pilus are encoded in a gene cluster, with PilA being the pilin subunit that is homologous with the Type IV pili from other organisms (Fig. A21-2) (Reguera et al., 2005). The pili have a diameter of 50 nm and can extend up to 20 μm from the cell surface (Revil et al., 2010). High electron transfer rates of 1011/s through the pili have been observed (El-Naggar et al., 2008). The nanowires can also connect multiple bacteria, implying that a community of cells can be wired for rapid electron transfer (Fig. A21-1) (Gorby et al., 2006). Beyond Geobacter, many other species have been shown to produce conductive pili in response to electron-acceptor limitation (Gorby et al., 2006).
Microbial fuel cells have emerged as a potential source of alternative energy (Gorby et al., 2006). A microbial fuel cell involves bacteria that are sequestered such that the only mechanism of electron transfer during respiration is to a graphite or gold anodes (Richter et al., 2008). The closest applications for microbial fuel cells are for long-term sensors deployed in the ocean and in wastewater treatment. Ocean sensors make use of the natural generation of electrical currents in the sea floor for power (Revil et al., 2010). Electricity can also be recovered from wastewater treatment as a byproduct of the breakdown of biomass. To deliver electricity to the anode, either a dissolved electron carrier or pili nanowires are required. Geobacter is one of the most efficient electron donors where it forms 50 μm thick biofilms on the surface (Revil et al., 2010). Pili are critical for electron transfer through the biofilm (Richter et al., 2008).
6. Environmental Sensing and Signal Processing
6.1. Physical Integrated Circuits: The Stressosome Bacillus subtilis (rsbR to rsbX)
One goal of synthetic biology is to build genetic circuits that can integrate information from environmental sensors or produce a dynamic response. To date, connecting circuits to form a program involves building a cascade at the level of transcription or translation. Each layer of the cascade requires about 20 min to complete (Hooshangi et al., 2005). More complex operations that require multiple layers can be particularly slow in the propagation of the signal. It would be much faster if the circuitry could be built as a molecular machine, where signals are directly received and signal integration occurs due to conformational changes or signal propagation (e.g., via a phosphorelay).
Bacteria have such a machine, known as the stressosome (Marles-Wright et al., 2008). In B. subtilis, it is in the gene cluster that contains many regulatory factors that converge on the anti-sigma factor σB, which controls the general stress response. This pathway integrates energy and environmental stresses through a complex partner-switching mechanism (Fig. A21-5) involving anti-sigma factors, anti-anti-sigma factors, kinases, and phosphatases, most of which occur together in a gene cluster (Fig. A21-2). Three of these proteins (RsbRST) form the structure of the stressosome, which is as large as a ribosome (1.8 MDa, 300 Å diameter) and appears as a spiked ball, with a core and protrusions (Fig. A21-1) (Marles-Wright and Lewis, 2010). The protrusions are composed of RsbR as well as four RsbR paralogs (Marles-Wright et al., 2008). The N-terminal domains of these proteins are variable, leading to the hypothesis that they act like sensors to receive diverse signals, including small molecules, protein-protein interactions, and even light (Marles-Wright and Lewis, 2010; Hecker et al., 2007). These signals are integrated by the core of the stressosome through conformational changes or other biochemical mechanisms. The RbsT protein interacts with the stressosome and transmits the signal to the σB pathway. The stressosome is induced by environmental stress and the release of RsbT is highly cooperative (a Hill factor of n=8). About 20 stressosomes are present in a single B. subtilis cell and they are closely associated with nucleoids and exhibit little diffusion. The σB gene cluster contains a number of other regulatory proteins that participate in partner-swapping and kinase/phosphatase interactions and there are internal transcriptional positive and negative feedback loops (Fig. A21-5). Together, this regulation ensures that the response is: (1) transient with a 30-min pulse of activity, (2) fast, (3) graded, and (4) the magnitude matches the degree of stress (Hecker et al., 2007; Igoshin et al., 2007).
The stressosome and the σB stress response pathway have several applications in biotechnology. The core proteins of the stressosome (RsbRST) are present in many species, including Gram negatives, and are associated with a variety of regulatory mechanisms, including aerotaxis, two-component sensors, and the biosynthesis of signaling molecules (Marles-Wright et al., 2008; Hecker et al., 2007). It may be that this structure is a common mechanism by which signals are integrated and understanding how to “reprogram” this structure would potentially enable much faster signal integration than transcriptional circuitry. In B. subtilis, there is evidence that five signals are integrated, but given the size of the structure, many more may be possible. The complete σB gene cluster is much less distributed than the stressosome. Several industrially relevant strains contain σB and related gene clusters, including Bacillus and Streptomyces (Hecker et al., 2007). The general stress response mediated by σB is involved with a number of stresses that are relevant to biotechnology, including response to shifts in salt concentration, pH, ethanol, ATP, cell wall stress, and UV light (Marles-Wright and Lewis, 2010). These types of stresses are common as the result of product accumulation, shifts in growth phase, and occur in different microenvironments in a bioreactor. Understanding how to rapidly integrate these signals would enable the construction of cell controllers that could regulate metabolic flux based on the changing environmental conditions of a fermentation.
6.2. An Immune System Against Phage: CRISPR Arrays Escherichia coli (cas3 to CRISPR4)
Many bacteria and archea contain an “immune system” that recognizes and intercepts foreign DNA based on previous exposure (Horvath and Barrangou, 2010; Marraffini and Sontheimer, 2010). This improves resistance against phage and the conjugative transfer of plasmid (Fig. A21-5). This function is encoded by a clustered, regularly spaced short palindromic repeat (CRISPR) region that occurs next to a gene cluster (Fig. A21-2). Each repeat spacer in the CRISPR region represents a DNA sequence of a phage or plasmid to which the bacteria have been exposed. The region is actively reprogrammed to respond to new challenges, which lead to the extension of the CRISPR region. Each repeat consists of a ~31-bp region of the targeted DNA and up to 374 repeats in a sinster (Marraffini and Sontheimer, 2010). Several genes are encoded in the cluster that form the Cas complex, which performs the tasks for the insertion of new spacer repeats and for the destruction of foreign DNA. The whole Cas-CRISPR cluster has undergone frequent horizontal transfer and some organisms have multiple clusters. An extreme example is Methanocaldoccus jannaschii, which contains 18 complete clusters with a total of 1188 repeat elements (Marraffini and Sontheimer, 2010).
CRISPR operates as an immune system by incorporating foreign DNA as a new repeat spacer and then recognizing this sequence in foreign DNA and destroying it (Fig. A21-5) (Horvath and Barrangou, 2010). The Cas complex cleaves foreign DNA and integrates it into the CRISPR region. The spacers are then transcribed together and processed into individual CRISPR RNAs (crRNAs), which associate with the Cas complex. The Cas-crRNA complex then recognizes the sequences in foreign DNA based on the crRNA sequence and the DNA is directed for degradation.
Bacteriophages are relevant in biotechnology as they are notorious for disrupting fermentations involving bacteria (Jones et al., 2000; Los et al., 2004). Traditionally, this is done through a process of “phage immunization” where resistant bacteria are identified through serial dilution of surviving cells (Jones et al., 2000). In one industrial example, dairy starter cultures of S. thermophilus were isolated and are now in use where phage resistance is conferred by CRISPR (Marraffini and Sontheimer, 2010). Bacteriophages have also been harnessed in biotechnology as agents for self-organization in the construction of materials (Flynn et al., 2003) and to be used as antibiotics (Sulakvelidze et al., 2001; Lu and Collins, 2007). For the latter, one of the issues that arises is rapid resistance that arises in the bacteria. In a study where bacteriophages were used to treat tooth decay, resistance in Streptococcus mutans occurred due to CRISPR immunity (van der Ploeg, 2009). The use of CRISPR elements has also been proposed as a mechanism to block the transfer of plasmids that confer antibiotic resistance and the horizontal transfer of pathogenicity islands that confer virulence (Horvath and Barrangou, 2010; Marraffini and Sontheimer, 2010).
6.3. Smelling Bacteria: Quorum Sensing Receiver Clusters Photorhabdus luminescens (yhfS to rafZ)
A nemotode (Heterorhabditis bacteriophora) implements biological warfare on its insect targets (Clarke and Photorhabdus, 2008). It has developed a symbiotic relationship with the bacterium P. luminescens to attack and digest a wide range of insects. The genome of the bacterium is filled with more toxins and virulence factors than any known organism (Duchaud et al., 2003). After the nemotode invades, the bacteria are released into the bloodstream where they kill and breakdown the host. P. luminescens is filled with gene clusters that encode multiple type I pili for adhesion, a type III secretion system, many toxin and virulence factor pathways, and 22 clusters that encode PKSs and NRPSs. These produce a variety of small molecules, including antibiotics that kill other bacteria that may compete for the dead insect’s nutritional resources.
Interestingly, the genome contains clusters of homologues to LuxR homologues—32 divided into two major clusters (Fig. A21-2) (Duchaud et al., 2003). In Vibrio fischeri, LuxR and LuxI participate in a quorum sensing circuit that enables bacteria to communicate (Waters and Bassler, 2005). LuxI is an enzyme that produces a small molecule (AI-1) that freely diffuses through the membrane. AI-1 accumulates and, when a threshold is crossed, it activates the response regulator LuxR. Many bacteria contain multiple orthogonal pairs of LuxI/LuxR homologues, which forms a sort of “language” by which cells can communicate (Fig. A21-5). Oddly, P. luminescens has many LuxR homologues, but no corresponding LuxI homologues (Duchaud et al., 2003). It has been postulated that the cluster of LuxR proteins may be there to sense many of the bacteria that would be competing for the nutrients available in the diseased insect. In addition, some of these sensors may have evolved to respond to host hormones, such as insect juvenile hormone, to determine the identity and developmental state of the insect (Wilkinson et al., 2009).
It is useful to be able to program communication between cells for a variety of applications biotechnology (Brenner et al., 2008). Quorum sensing provides a language by which this can be achieved, where each chemical signal represents a channel for communication (Waters and Bassler, 2005). The LuxI enzyme is a “sender device” that produces the signal and LuxR is a “receiver device” that responds to the signal (Basu et al., 2005). When these devices are separated between cells, this enables cells to communicate. This has been used to program cells to form patterns, including bull’s eyes (Fig. A21-5) (Basu et al., 2005) and to implement an edge detection algorithm (Tabor et al., 2009). More direct applications in biotechnology have been proposed for quorum sensing, including controlling the density of a population of bacteria in a fermentor and killing cancer cells once an invading population crosses a threshold density (Brenner et al., 2008; Anderson et al., 2006).
In this review, we have attempted to capture the diversity of functions that are encoded in gene clusters. All of these have many potential applications in biotechnology. Achieving this potential will require methods that enable the reliable re-engineering of clusters. To date, this has been challenging because of the size of clusters, the number of genetic parts that are involved, and the complexity of the genetic regulation. Recently, progress in genetic engineering has increased the scale of projects that are achievable. Synthetic biology has emerged as a field and libraries have been populated with genetic “parts” that can carefully control transcription and translation and “devices” that encode regulatory sensors and circuits. Methods have been developed for the rapid assembly of these parts on the scale of gene clusters, and methods exist to ultimately combine multiple clusters into a host. Together, these advances will enable the bottom-up assembly of synthetic gene clusters to simplify and optimize their function. Beyond functions that are naturally organized in clusters, it will be interesting if the design principles from studying these systems could be applied to other functions—such as the flagellum—to create similarly transferable units. This may move genetic engineering to an era of genome design where simplified gene clusters are combined in order to pull together functions from many diverse organisms to build a synthetic one.
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Reprinted with permission from Fischbach, M., and Voigt, C. A: Prokaryotic gene clusters: A rich toolbox for synthetic biology. Biotechnology Journal 2010. 5. 1277–1296. Copyright Wiley-VCH Verlag GmbH & Co. KGaA. Reproduced with permission.
Department of Bioengineering and Therapeutic Sciences, University of California–San Francisco, San Francisco, CA, USA.
Department of Pharmaceutical Chemistry, University of California–San Francisco, San Francisco, CA, USA.
Correspondence: Professor Christopher A. Voigt, Department of Pharmaceutical Chemistry, University of California – San Francisco, MC 2540, Room 408C, 1700 4th Street, San Francisco, CA 94158, USA.
E-mail: moc.liamg@tgiovac Fax: +1-415-502-4690
Abbreviations: PCB, polychlorinated biphenyls; PHA, poly(hydroxyalkanoate); PHB, poly(3-hydroxybutyrate)
Keywords: Biotechnology·Devices·Genetic parts·Refactoring·Systems biology
This work was funded by NIH grant R01 AI067699. The authors have declared no conflict of interest.
National Academies Press (US), Washington (DC)
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