Engineering biofuel tolerance in non-native producing microorganisms Hu Jin, Lei Chen, Jiangxin Wang, Weiwen Zhang PII: DOI: Reference:

S0734-9750(14)00020-2 doi: 10.1016/j.biotechadv.2014.02.001 JBA 6788

To appear in:

Biotechnology Advances

Received date: Revised date: Accepted date:

23 October 2013 19 January 2014 8 February 2014

Please cite this article as: Jin Hu, Chen Lei, Wang Jiangxin, Zhang Weiwen, Engineering biofuel tolerance in non-native producing microorganisms, Biotechnology Advances (2014), doi: 10.1016/j.biotechadv.2014.02.001

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ACCEPTED MANUSCRIPT Engineering biofuel tolerance in non-native producing

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microorganisms

Laboratory of Synthetic Microbiology, School of Chemical Engineering &

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Hu Jin 1, 2, 3, Lei Chen 1, 2, 3, Jiangxin Wang 1, 2, 3, Weiwen Zhang 1, 2, 3, *

Technology, Tianjin University, Tianjin 300072, P.R. China; 2 Key Laboratory of

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Systems Bioengineering, Ministry of Education, Tianjin 300072, P.R. China; 3

China

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Collaborative Innovation Center of Chemical Science and Engineering, Tianjin, P.R.

* To whom correspondence should be addressed: Prof. Dr. Weiwen Zhang

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Laboratory of Synthetic Microbiology School of Chemical Engineering & Technology Tianjin University Tianjin 300072, P. R. China Tel : 0086-22-2740-6394; Fax: 0086-22-2740-6364 Email: [email protected]

Running title: Biofuel tolerance in non-native producing microbes

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ACCEPTED MANUSCRIPT ABSTRACT Large-scale production of renewable biofuels through microbiological processes has

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drawn significant attention in recent years, mostly due to the increasing concerns on

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the petroleum fuel shortages and the environmental consequences of the over-utilization of petroleum-based fuels. In addition to native biofuel-producing microbes that have been employed for biofuel production for decades, recent

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advances in metabolic engineering and synthetic biology have made it possible to

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produce biofuels in several non-native biofuel-producing microorganisms. Compared to native producers, these non-native systems carry the advantages of fast growth,

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simple nutrient requirements, readiness for genetic modifications, and even the

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capability to assimilate CO2 and solar energy, making them competitive alternative

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systems to further decrease the biofuel production cost. However, the tolerance of these non-native microorganisms to toxic biofuels is naturally low, which has

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restricted the potentials of their application for high-efficiency biofuel production. To address the issues, researches have been recently conducted to explore the biofuel tolerance mechanisms and to construct robust high-tolerance strains for non-native biofuel-producing microorganisms. In this review, we critically summarize the recent progress in this area, focusing on three popular non-native biofuel-producing systems, i.e. Escherichia coli, Lactobacillus and photosynthetic cyanobacteria.

Keywords:

Biofuels;

Tolerance;

Metabolic

Lactobacillus; Cyanobacteria

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Engineering;

Escherichia coli;

ACCEPTED MANUSCRIPT 1. Introduction High oil prices and growing concerns over energy security and climate change are

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driving investment and innovation in the area of renewable biofuels in recent years

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(Hill et al., 2006; Kerr, 2005). In addition to bioethanol that has been commercially used as a gasoline replacement in major markets of the world, other biofuel products with better physical and chemical properties, such as 1-butanol, isobutanol, alkanes,

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alkenes and biodiesel are also being pursued as promising alternatives (Connor and

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Atsumi, 2010; Wang et al., 2012a; Zhang et al., 2011). Traditionally, biofuels such as ethanol and butanol are produced through fermentation of native-producing microbes

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such as yeast Saccharomyces cerevisiae, bacterium Zymomonas mobilis and

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Clostridium acetobutylicum (Lee et al., 2008b; Lin and Tanaka, 2006). Although

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significant progresses have been made in the past decades as many parameters such as inhibitor sensitivity, total yield, specific productivity and product tolerance were

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significantly improved in modern industrial strains (Antoni et al., 2007), these native producing microorganisms still have some less-satisfied properties, such as relatively slow growth rate, complex nutrient requirements and complex life cycle (i.e., spore-forming in Clostridium). In addition, in some native producing microbes, the same biochemical process of biofuel synthesis often creates a number of by-products, such as hydrogen, acetic, lactic and propionic acids, acetone, isopropanol and ethanol in butanol-producing Clostridium, which increases the cost of downstream product purification (Green, 2011; Lütke-Eversloh and Bahl, 2011; Zheng et al., 2009). Moreover, some of native producing strains are reluctant to genetic manipulation and

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ACCEPTED MANUSCRIPT so there exist technical challenges for further engineering them by various genetic and synthetic biology strategies (Mukhopadhyay et al., 2008). To address these issues,

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pioneer efforts have been made recently to introduce biofuel production pathways into

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microbes that are more amenable to genetic manipulation, and not capable of producing biofuels in their native forms, such as Escherichia coli, Lactobacillus, Pseudomonas putida, Bacillus subtilis and even photosynthetic microbes, such as

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cyanobacteria (For the details refer to several excellent reviews published recently

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(Dexter and Fu, 2009; Lan and Liao, 2012a; Schirmer et al., 2010; Tan et al., 2011)). Compared to the native biofuel producing microbes, these non-native microbes often

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have fast growth rates, well-characterized genetic background, well-established

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genetic manipulation systems, and more economically viable large-scale production

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processes (Lee et al., 2008a; Ranganathan and Maranas, 2010; Mainguet et al., 2013). For cyanobacteria, as they can produce biofuels by utilizing solar energy and CO2 as

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the sole energy and carbon sources, respectively (Ducat et al., 2011; Robertson et al., 2011), they may represent an important alternative to biomass-based biofuel production which may potentially compete with world food supply and cause economic and ethical problems. Most of biofuels are known to cause damages to cell structure and functions of microbes (Ramos et al., 2002). For example, cell membrane involves a variety of physiological processes, such as maintaining cell morphology, transporting solute and electron, and signal transduction (Huffer et al., 2011; Isken and de Bont, 1998), the accumulation of biofuels, such as ethanol, butanol and hexane, in cell membrane can

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ACCEPTED MANUSCRIPT lead to significant changes in the membrane integrity, structures (i.e., permeability and fluidity) and physiological functions (Bowles and Ellefson, 1985; Ding et al.,

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2009; Sikkema et al., 1995). In addition, biofuel exposure can also change the internal

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pH in cells and further affect various biochemical reactions important to cellular metabolism, eventually leading to growth inhibition and even cell death (Nicolaou et al., 2010). It has been found that the biofuel toxicity to cells is inversely correlated

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with the logPow value, which is the common logarithm of the partition coefficient (Pow)

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for the distribution of the organic solvent between n-octanol and water phases (Hansch and Anderson, 1967; Harnisch et al., 1983). For several widely used native

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biofuel-producing microorganisms, such as yeast and Clostridium, the cellular

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tolerance mechanisms to biofuels have been well described (Alsaker et al., 2010; Ding

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et al., 2009; Tomas et al., 2004). The results showed that the microbial cells tend to employ a combination of multiple cellular changes, including modification of cell

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membrane and wall, induction of multiple transporters and cell mobility-related proteins, in addition to common stress responses typical to all microbes (i.e., heat shock proteins) as protection mechanisms against biofuel toxicity. These typical biofuel responses have been extensively summarized in two recent review articles (Nicolaou et al., 2010; Dunlop, 2011). Based on these cellular responses, various strategies including mutant screening and genetic engineering have been applied to generate biofuel-tolerant strains (Dunlop, 2011; Lo et al., 2013), and their applications have been demonstrated as a very efficient way to increase biofuel production in industry (Kim et al., 2011; Qi et al., 2011; Shao et al., 2011). Compared with native

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ACCEPTED MANUSCRIPT biofuel-producing microorganisms, currently very little is known about the tolerance mechanism in non-native systems. Meanwhile, the natural tolerance of non-native

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systems is typically 1-2 order of magnitude lower than some of the native producers,

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for example, some industry yeast strains can grow under 25% (v/v) ethanol (Shi et al., 2009); while growth of E. coli and cyanobacterial Synechocystis sp. PCC 6803 will be highly inhibited by only 3% and 1.5% of ethanol, respectively (Wang et al., 2012b;

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Wang et al., 2013). To support the synthetic biology efforts of constructing

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high-efficiency biofuel producing strains in non-native microbial systems (Kim et al., 2013; Lee et al., 2013), in the past several years, researches have been conducted in

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identifying biofuel response mechanisms in non-native microorganisms, which helps

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build an important knowledge foundation for further rational engineering of more

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robust biofuel-producing systems in these microorganisms. We herein summarize the progresses on biofuel tolerance investigating and engineering in three major

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non-native hosts, E. coli, Lactobacillus and photosynthetic cyanobacteria.

2. Escherichia coli As one of the best-characterized microbes, E. coli has been the most favorable genetic engineering hosts for many biotechnological applications. Recent synthetic biology efforts have led to several successful reports of biofuel production in engineered E. coli strains, including ethanol (Dien et al., 2003), n-butanol, isobutanol (Lan and Liao, 2012a), higher-chain alcohols (Lamsen and Atsumi, 2012), alkanes (Schirmer et al., 2010), free fatty acids (Lu et al., 2008), biodiesel (Kalscheuer et al., 2006) and

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ACCEPTED MANUSCRIPT hydrogen (Penfold et al., 2003). Although these studies have demonstrated the feasibility and potentials of applying E. coli system for biofuels production, the

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overall productivity is still very low, currently at levels of 34-63.2 g/L for ethanol,

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0.001-30 g/L for n-butanol and 4-50 g/L for isobutanol, respectively (Dien et al., 2003; Lan and Liao, 2012a), which are at least one order of magnitude lower than the productivities in their native-producing systems (Weber et al., 2010). Although low

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productivity could be ascribed to many factors, from codon usage efficiency at gene

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level to enzymatic activity and stability at protein level, low tolerance to products/biofuels is definitely one of the key factors that deserve further attention.

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Towards the goal of improving biofuel tolerance in E. coli, global-level analyses of E.

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coli stress responses under various exogenous biofuels were performed (Atsumi et al.,

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2010; Brynildsen and Liao, 2009; Minty et al., 2011; Reyes et al., 2011; Rutherford et al., 2010), and the identified mechanisms related to biofuel tolerance have been

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applied to guide the construction of E. coli biofuel-tolerant strains. Transporters play an important role in biofuel tolerance. Okochi et al. (2007) performed a time-course gene expression profiling of solvents-exposed E. coli and found that the expression level of manXYZ operon that encodes a sugar transporter of the phosphotransferase system was strongly up regulated. Overexpression of manXYZ led to the increased tolerance against hexane or the mixture of hexane and cyclohexane (Okochi et al., 2007). By screening coexisting genomic libraries of fosmids (large inserts) and plasmids (smaller inserts) under increasing ethanol concentrations, Nicolaou et al. (2012) were able to identify interacting genetic loci

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ACCEPTED MANUSCRIPT imparting ethanol tolerance in E. coli, and co-expression of two identified genomic fragments (sfsB, murA, yrbA, mlaB, mlaC, mlaD, mlaE, mlaF, and yrbG) and (yrbA,

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mlaB, and mlaC) enhanced E. coli survival to 50 g/L ethanol by up to 115% (Nicolaou

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et al., 2012). Among the genes involved, the mla operon encodes an ABC transporter with a role in trafficking of phospholipids from the outer membrane toward the inner membrane, thus reducing the permeability of the outer membrane to maintain

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resistance to chemicals (Malinverni and Silhavy, 2009). Efflux pumps are also known

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for their roles in maintaining tolerance against solvents (Nicolaou et al., 2010). Efflux pump acrAB-tolC provides tolerance to alkanes, alkenes, cyclichydrocarbons, and

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longer alcohols in E. coli (Nicolaou et al., 2010; Dunlop, 2011). Early study found

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that overexpression of regulatory protein MarA increased the tolerance to geraniol in

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E. coli, which may be attributed to its regulatory role on the AcrAB-TolC efflux pump (Shah et al., 2013). In addition, deletion of marR encoding a repressor of mar operon

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was found to increase the cell tolerance to hexane (Doukyu et al., 2012). Although recent studies suggested that efflux pumps may not be effective at exporting short-chain alcohols, and may even reduce cell tolerance in some cases (Dunlop, 2011), over-expression of an efflux pump encoded by focA enhanced n-butanol tolerance in E. coli (Reyes et al., 2011). To improve the efficiency of over-expressed transporters or efflux pumps, Foo and Leong (2013) adapted a strategy of directed evolution of native transporters, accompanied with a selection platform based on competitive growth using a toxic substrate surrogate, which allowed a rapid selection of AcrB variants showing enhanced efflux of linear and cyclic fuel molecule

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ACCEPTED MANUSCRIPT candidates, n-octane and α-pinene, and two mutants exhibiting increased efflux efficiency for n-octane and α-pinene by up to 47% and 400%, respectively, were

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isolated (Foo and Leong, 2013). Similarly, Fisher et al. (2013) applied a directed

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evolution strategy to generate variants of AcrB efflux pump that acts on the non-native substrate n-butanol, enhancing growth rates of E. coli in the presence of n-butanol by up to 25%. Furthermore, these variants conferred improved tolerances to

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isobutanol and straight-chain alcohols up to n-heptanol (Fisher et al., 2013). To further

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identify novel biofuel pumps from a broad range of microorganisms, Dunlop et al. (2011) applied bioinformatics approach to generate a list of all efflux pumps from the

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sequenced bacterial genomes and prioritized a subset of 43 pump targets for cloning

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and heterologous expression in E. coli. By using a competitive growth assay, the

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researchers efficiently distinguished pumps that improved E. coli survival under biofuel stress (Dunlop et al., 2011). More recently, Doshi et al. (2013) demonstrated

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that membrane-embedded transporters, better known to efflux lipids and drugs, could be used to mediate the secretion of intracellularly synthesized model isoprenoid biofuel compounds to the extracellular milieu. Transporter-mediated biofuel secretion sustainably maintained an approximate three- to fivefold boost in biofuel production in the tested E. coli test system (Doshi et al., 2013). As the first resistance barrier against environmental stresses, changes of cell wall or cell membrane can affect cell tolerance to biofuels (Sikkema et al., 1995). For example, overexpression of the murEF and murB genes in the mur operon that is involved in cell wall biosynthesis led to tolerance increase against ethanol by 160%

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ACCEPTED MANUSCRIPT and 65%, respectively (Goodarzi et al., 2010; Nicolaou et al., 2012). Lipopolysaccharide is one the of major cell wall components in Gram-negative

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bacteria. Reyes et al. (2012) and Woodruff et al. (2012) found that the

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lipopolysaccharide biosynthesis genes were up-regulated by biofuel stress in E. coli (Reyes et al., 2012; Woodruff et al., 2012). The imp gene, also called ostA due to its relationship with organic solvent tolerance, is involved in cell-wall biosynthesis and

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membrane permeability in cells, overexpression of the imp gene conferred n-hexane

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resistance to the E. coli strain sensitive to n-hexane (Abe et al., 2003). Early studies have found that changing fatty acid composition of cell membrane can improve

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solvent tolerance in microbes (Kajiwara et al., 2000; Zhao et al., 2003). One

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well-characterized membrane modification is the shift from cis to trans unsaturated

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fatty acids to decrease membrane fluidity under solvent stress (Dunlop, 2011). To investigate the effects of cellular fatty acids composition on ethanol tolerance in E.

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coli, Luo et al. (2009) overexpressed the fabA gene encoding beta-hydroxydecanoyl thioester dehydrase from E. coli, or the fabA gene together with the des gene encoding fatty acid desaturase from B. subtilis in E. coli, and found a elevated tolerance against ethanol by about 50 and 10%, respectively, when compared to the wild-type strain (Luo et al., 2009). The role of the fabA gene in ethanol tolerance was also confirmed recently by a study using a multiscalar analysis of library enrichments (SCALEs) method and a growth selection to map genes involved in ethanol tolerance and production (Woodruff et al., 2013). Jeong et al. (2012) recently showed that the mutated fabF which encodesβ-ketoacyl-ACP synthases led to a two-fold increase in

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ACCEPTED MANUSCRIPT cis-vaccenic acid (18:1), associating with more than 50% improvement of 1-butanol tolerance (Jeong et al., 2012), consistent with a previous finding that high ethanol

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tolerant Z. mobilis strain contained over 75% vaccenic acid in polar lipids of its

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membranes (Nicolaou et al., 2010). The results suggested unsaturated fatty acid vaccenic acid could contribute positively to the tolerance to short-chain alcohol biofuels.

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Heat shock proteins are part of common stress networks involved in stress

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responses to many environmental perturbations in E. coli (Aertsen et al., 2004; Jenkins et al., 1988; Winter et al., 2005). Recent transcriptomic and proteomic studies

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found that heat shock proteins were up-regulated in response to ethanol, n-butanol and

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isobutanol stress (Brynildsen and Liao, 2009; Horinouchi et al., 2010; Rutherford et

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al., 2010). In addition, their roles in biofuel tolerance were also demonstrated by over-expression of heat shock proteins in E. coli. For example, Zingaro and

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Papoutsakis (2012) examined the impact of overexpressing the autologous GroESL chaperone system with its natural promoter on the tolerance of E. coli to several toxic alcohols, and found that GroESL over expression enhanced cell growth to all alcohols tested, including a 12-fold increase in total growth in 48-h cultures under 4% (v/v) ethanol, a 2.8-fold increase under 0.75% (v/v) n-butanol, a 3-fold increase under 1.25% (v/v) 2-butanol, and a 4-fold increase under 20% (v/v) 1,2,4-butanetriol (Zingaro and Terry Papoutsakis, 2012). In another study, Reyes et al. (2011) identified 11 genes that conferred significant increase in n-butanol tolerance when overexpressed; interestingly, three of the 11 genes (i.e., yibA, metA and ymcE) were heat shock

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ACCEPTED MANUSCRIPT related genes (Reyes et al., 2011). In addition to engineering individual gene or enzyme to improve biofuel tolerance,

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increasing studies were recently conducted using regulatory genes or proteins as

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targets for biofuel-tolerance improvements, as more evidence suggested that the manipulation of regulatory genes could provide a route to complex phenotypes that are not readily accessible by traditional methods of targeting some number of

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metabolic genes (Alper and Stephanopoulos, 2007; Petranovic and Vemuri, 2009; Tyo

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et al., 2007). For example, expression of a mutated global regulator gene irrE from an extremely radiation-resistant bacterium, Deinococcus radiodurans, led to 10- to

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100-fold enhancement of E. coli tolerances to ethanol or butanol in shock experiments

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(Chen et al., 2011); and error-prone PCR based engineering of a native global

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transcription factor cAMP receptor protein (CRP), which is known to regulate over 400 genes in E. coli, resulted in ethanol-tolerant CRP mutants with a higher growth

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rate in 62 g/L ethanol and a higher survival rate in 150 g/ L ethanol (Chong et al., 2013b), and isobutanol-tolerant mutant that exhibits much better growth (0.18 h−1) than the control (0.05 h−1) in 1.2% (v/v) isobutanol (9.6  g/L) (Chong et al., 2013a). In addition to regulatory genes, manipulating the expression of noncoding small regulatory RNAs (sRNAs) has also been proposed as an alternative strategy for tolerance improvement. By simultaneously overexpressing several sRNAs, DsrA, RprA and ArcZ which are translational RpoS activators, Gaida et al. (Gaida et al., 2013) achieved tolerance increase against acid (based on a low-pH survival assay) by up to 8500-fold during active cell growth, and provided protection to cells against

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ACCEPTED MANUSCRIPT carboxylic acid and oxidative stress. Moreover, unlike the overexpression of proteins, overexpression of sRNAs imposes hardly any metabolic burden on cells, and

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constitutes a potentially more effective strain-improvement strategy (Gaida et al.,

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2013). In another recent study, Na et al. (2013) designed synthetic sRNAs to identify and modulate the expression of target genes for metabolic engineering in E. coli. Using a library of 130 synthetic sRNAs, the researchers were able to identify

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chromosomal gene targets that enabled substantial increases in cadaverine production

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(Na et al., 2013). Although so far no study has been reported on applying the sRNAs strategy directly for biofuel tolerance improvement, early studies have demonstrated

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that the design principles and the engineering strategy using synthetic sRNAs are

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traits (Na et al., 2013).

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generalizable to various bacteria and applicable in developing various physiological

To fully elucidate the complex molecular mechanisms associated with biofuel

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tolerance in E. coli, it is necessary to include functional characterization and accurate quantification of all levels of gene products, i.e., mRNA, proteins and metabolites. In a recent study, Wang et al. (2013) applied a gas chromatography-mass spectrometry (GC-MS)

based

metabolomics

to

determine

both

the

time-series

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concentration-series metabolomic responses of E. coli to three major biofuel products, ethanol, butanol and isobutanol; and then applied the weighted correlation network analysis (WGCNA) approach to metabolomic data to reveal active metabolic modules associated with each biofuel stress (Wang et al., 2013). The results showed that the cellular responses caused by the biofuel stress were in general similar to aging cells at

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ACCEPTED MANUSCRIPT stationary phase. In addition, the WGCNA analysis of the metabolomics data allowed identification of 2, 4 and 2 metabolic modules specifically associated with ethanol,

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butanol and isobutanol treatments, respectively. The biofuel-associated modules

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included amino acids and osmoprotectants, such as isoleucine, valine, glycine, glutamate and trehalose, suggesting amino acid metabolism and osmoregulation are among the key protection mechanisms against biofuel stresses in E. coli. Interestingly,

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no module was found associated with all three biofuel products, suggesting

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differential effects of each biofuel on E. coli. The study also demonstrated the effectiveness of the metabolomic and network analysis in identifying targets for

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3. Lactobacillus

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biofuel tolerance (Wang et al., 2013).

Early studies showed that L. heterohiochii and L. homohiochii strains were able to

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grow in media supplemented with 18% (v/v) ethanol (Ingram, 1989), while L. delbrueckii and L. brevis strains can grow in the media supplemented with up to 3% butanol (Knoshaug and Zhang, 2009), suggesting that the genus Lactobacilli contained microbial species with the most biofuel tolerance capability (López et al., 2004; Liu et al., 2008). The relatively high tolerance of Lactobacilli to biofuels makes them a very promising non-native host system for high-efficiency biofuel production. Recently several studies were reported in using synthetic biology and metabolic engineering approaches to modify Lactobacilli strains for biofuel production (Berezina et al., 2010; Gold et al., 1996; Liu et al., 2007; Liu et al., 2006; Liu et al.,

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ACCEPTED MANUSCRIPT 2008). Gold et al. (1996) cloned and expressed the genes coding for pyruvate decarboxylase (pdc) and alcohol dehydrogenase (adh) from Z. mobilis in L. casei 686,

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achieving more than two-folds increase of ethanol production, compared with the

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parental L. casei 686 strain (Gold et al., 1996). Berezina et al. (2010) cloned the bcs-operon and the thl gene encode the enzymes of the lower part of the clostridial butanol pathway (i.e., crotonase, butyryl-CoA-dehydrogenase, two subunits of the

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electron transfer flavoprotein, 3-hydroxybutyryl-CoA dehydrogenase, and thiolase)

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from C. acetobutylicum, and expressed them in L. brevis, achieving up to 300 mg/L or 4.1 mM of butanol production on a glucose-containing medium (Berezina et al., 2010).

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Currently biofuel productivity in the Lactobacilli systems is still very low, and further

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improvements from various aspects, including tolerance increase, are necessary.

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With many Lactobacilli species genomes sequenced (de Lucena et al., 2012; Kleerebezem et al., 2003; Zhang et al., 2009), efforts have been taken to investigate

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the global stress responses against various environmental stresses, such as acid, lactate, oxidative, bile, and heat stresses in Lactobacilli (van Bokhorst-van de Veen et al., 2011); however, so far very little information is available on molecular mechanisms related to biofuel tolerance in Lactobacilli. Van Bokhorst-van de Veen et al. (2011) recently determined the adaptation of L. plantarum WCFS1 to the presence of 8% (v/v) ethanol over short (10-min and 30-min) and long (24-h) time intervals using DNA microarrays, and identified a total of 57 genes differentially expressed at all time points, including canonical stress response pathways controlled by the central stress regulators HrcA and CtsR. To evaluate the role of HrcA and CtsR in ethanol

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ACCEPTED MANUSCRIPT tolerance, ctsR and hrcA gene deletion mutants were constructed. Further analysis showed that the growth rate of the L. plantarum ΔctsR::cat strain was impaired in the

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de Man-Rogosa-Sharpe (MRS) medium containing 8% (v/v) ethanol, whereas growth

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of the L. plantarum ΔhrcA::cat and ΔctsR ΔhrcA::cat mutants was indistinguishable from that of wild-type cells (van Bokhorst-van de Veen et al., 2011). In an early study, Couto et al. (1997) evaluated the survival of a highly ethanol-tolerant L. hilgardii, and

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found that pre-treatment of the cells with ethanol can increase the cell growth under

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ethanol stress by several log cycles (Couto et al., 1997). In addition, temperature upshift (25 to 40°C) before ethanol challenge also showed the similar enhancement of

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apparent resistance to ethanol, suggesting a common stress response mechanism may

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be involved in biofuel tolerance in Lactobacilli (Couto et al., 1997). Consistently,

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recent studies revealed that heat shock proteins were typically up-regulated by ethanol or n-butanol stress in Lactobacilli (van Bokhorst-van de Veen et al., 2011; Winkler

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and Kao, 2011). Overexpression of GroESL or small heat shock proteins led to an enhanced survival in the presence of butanol or ethanol in L. paracasei strains (Desmond et al., 2004; Fiocco et al., 2007; Sugimoto et al., 2010) . Similar to the responses in E. coli，changes of cell wall and cell membrane were also found in biofuel-resistant Lactobacilli. Genes related to cell wall biosynthesis, such as dlt operon required for D-alanylation of teichoic acids, tagE5 and tagE6 possibly involved in teichoic acid biosynthesis, were up-regulated by ethanol (van Bokhorst-van de Veen et al., 2011). The fatty acid composition of the cell membrane and the ratio of unsaturated to saturated fatty acids were also regulated by ethanol

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ACCEPTED MANUSCRIPT stress (van Bokhorst-van de Veen et al., 2011). For example, Winkler and Kao (2011) detected the upregulation of the fatty acid synthetic pathway under n-butanol stress in

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L. brevis, which may act to stabilize membrane in resisting the fluidization induced by

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n-butanol (Winkler and Kao, 2011). In addition, n-butanol challenge can reduce the proportion of 19:1 cyclopropane fatty acid within the L. brevis cell membrane (Winkler and Kao, 2011), consistent with the similar finding in the evolved E. coli

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strains under isobutanol stress (Minty et al., 2011). Cyclopropane fatty acids were

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suggested to be involved in stabilizing membrane lipids against turnover and degradation and in cell membrane fluidity (Montanari et al., 2010), and have been

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suggested to play an important role in response to acid, oxidative, thermal and

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osmotic stress in various microbes (Guerzoni et al., 2001; Guillot et al., 2000), such as

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E. coli (Chang and Cronan, 1999), P. putida (Muñoz-Rojas et al., 2006), Oenococcus oeni (Teixeira et al., 2002) and Lactobacilli (Montanari et al., 2010; Winkler and Kao,

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2011). The proposed function of cyclopropane fatty acid in biofuel tolerance was further confirmed by a recent study by Reyes et al. (2012) who found that the overexpression of cyclopropane fatty acid in E. coli increased the tolerance to n-butanol (Reyes et al., 2012). To take advantage of the high biofuel tolerance of Lactobacillus, Winkler et al. (2010) generated hybrid strains between E. coli and L. brevis via protoplast fusion, and found that the hybrid strains tolerated up to 2% (v/v) butanol compared to the 1% (v/v) maximum for E. coli. In addition, the growth inhibitory effects of butanol were also significantly less in several hybrids compared to E. coli (Winkler et al., 2010).

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4. Cyanobacteria

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Photosynthetic cyanobacteria have attracted significant attention recently as a

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“microbial cell factory” to produce renewable biofuels and fine chemicals due to their capability to utilize solar energy and CO2 as the sole energy and carbon sources, respectively (Machado and Atsumi, 2012; Wang et al., 2012a). Cyanobacteria possess

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some properties that have endowed them with the ability to be one of the most

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promising candidates for biofuel production. Cyanobacteria grow easily with basic nutritional requirements, and contain considerable amounts of lipids in the thylakoid

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membranes and possess higher photosynthetic efficiency and faster growth rate

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compared to other green algae and higher plants (Quintana et al., 2011). In addition,

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cyanobacteria have relatively simple genetic background and well-characterized tools for genetic manipulation. Both integrative and replicative plasmids vectors have been

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developed for cyanobacteria (Wang et al., 2012a). With the genome sequencing of 80 cyanobacteria

species

completed

so

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(www.ncbi.nlm.nih.gov/genome/?term=cyanobacteria), the studies for a better understanding of cyanobacterial physiology and genetics, and their potential applications can be accelerated through various high-throughput post-genomics and synthetic biology technologies. So far there are two approaches to utilize cyanobacteria for biofuel production (Liu et al., 2012): separate fatty acids from lipid-rich cyanobacterial biomass and then convert them chemically to other products, or employ engineered cyanobacteria to produce desired biofuel directly. The latter one

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ACCEPTED MANUSCRIPT is more feasible in large-scale commercial application because the lipid extraction process is energy-intensive (Sheng et al., 2011). Recent reports have showed

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successful production of various biofuels in engineered cyanobacteria systems by

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synthetic biology and metabolic engineering efforts, including ethanol, 1-butanol, isobutanol, alkanes, alkenes, free fatty acids, biodiesel, and hydrogen (Wang et al., 2012a). Although the current productivity level is very low, these reports

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demonstrated that the large-scale production of biofuels from cyanobacteria could be

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achievable in the near future.

One of the crucial factors responsible for the low biofuel productivity of

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cyanobacteria cells is their low tolerance to toxic biofuel (Dunlop, 2011; Nicolaou et

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al., 2010). Recent studies in the model system Synechocystis sp. PCC 6803 showed

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that 50% of the growth could be arrested by ethanol, butanol and hexane at a concentration of 1.5%, 0.2% and 0.8% (v/v), respectively (Liu et al., 2012; Qiao et al.,

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2012; Tian et al., 2012). In addition, flow cytometric analysis study showed that ethanol-treated cells tended to aggregate after 24 h treatment even at a low concentration of 1.5% (v/v) ethanol (Qiao et al., 2012). Kämäräinen et al. (2012) recently evaluated factors which could potentially limit economic sustainability of engineered cyanobacteria: i) tolerance of the host to the intended end-product, and ii) stoichiometric potential for production. The results showed externally added alcohols inhibited cyanobacterial growth the most, followed by aldehydes and acids, while alkanes were the least inhibitory. The growth inhibition became progressively greater with increasing chain-length for alcohols, while the intermediate C6 alkane caused

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ACCEPTED MANUSCRIPT more inhibition than both C3 and C11 alkane. In addition, Synechocystis sp. PCC 6803 was more tolerant to some of the tested chemicals than Synechococcus elongatus

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PCC 7942, particularly ethanol and undecane (Kämäräinen et al., 2012). Currently the

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knowledge on biofuel tolerance mechanisms in cyanobacteria is very limited. To address the issue, several studies using systems biology approach to explore the biofuel tolerance mechanisms and to construct biofuel-tolerant strains were conducted

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in cyanobacteria.

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Ethanol tolerance: In two early studies, heterologous expressing pyruvate decarboxylase (pdc) and alcohol dehydrogenase (adh) from the bacterium Z. mobilis

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in Synechococcus elongatus PCC 7942 and Synechocystis sp. PCC 6803 resulted in

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230 mg/L and 550 mg/L ethanol production, respectively (Deng and Coleman, 1999;

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Dexter and Fu, 2009). Recently Fu (2009) constructed a genome-scale metabolic network model of Synechocystis sp. PCC 6803 and its application led to the ethanol

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production improvement to up to 690 mg/L in a week (Fu, 2009). More recently, Gao et al. (2012) constructed an engineered Synechocystis sp. PCC 6803 strain by introducing the pdc gene from Z. mobilis and overexpressing endogenous adh gene through homologous recombination at two different sites of the chromosome, and simultaneously disrupting the biosynthetic pathway of poly-β-hydroxybutyrate (PHB). The engineered strain can achieve direct conversion from CO2 to ethanol with significantly higher ethanol-producing efficiency (5.50 g/L, 212 mg/L . day) (Gao et al., 2012). To explore the mechanisms of ethanol tolerance so that engineering more robust

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ACCEPTED MANUSCRIPT cyanobacterial hosts can be possible, Qiao et al. (2012) determined the cellular responses of Synechocystis sp. PCC 6803 to ethanol by applying quantitative iTRAQ

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LC-MS/MS proteomics approach. The functional analysis showed that Synechocystis

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sp. PCC 6803 cells employed a combination of cell wall and membrane modifications, induction of multiple transporters and heat shock proteins, as well as induced common stress response, and induction of cell mobility-related proteins as major

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protection mechanisms against ethanol. Interestingly, the comparative proteomic

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analysis provided strong evidences that proteins involved in multiple aspects of photosynthesis (i.e., photosystems I and II, cytochrome, ferredoxin) were up-regulated

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in ethanol-treated Synechocystis, which is inconsistent with some early studies

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showing the photosynthetic activity was generally decreased upon environmental

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stresses, such as salt and sulfur starvation (Allakhverdiev and Murata, 2008; Zhang et al., 2008). As a unique biochemical property for photosynthetic organisms, it remains

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unclear how the increased expression of photosynthesis-related proteins will help combat the ethanol toxicity (Qiao et al., 2012), although it is speculative that ethanol treatment might enhance photosynthesis in Synechocystis or impair photosynthesis thus cause up-regulation of related proteins as compensation, with generation of highly reactive oxygen species (ROS) and then trigger oxidative stress response in the end (Fig. 1). In addition, Wang et al. (2013) applied a quantitative RNA-seq transcriptomics approach, combined with quantitative reverse-transcript PCR (RT-qPCR) analysis, to reveal responses to ethanol at transcriptional level. The results showed that ethanol exposure induced genes involved in common stress responses,

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ACCEPTED MANUSCRIPT transporting and cell envelope modification. In addition, the cells can also utilize enhanced polyhydroxyalkanoates (PHA) accumulation and glyoxalase detoxication

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pathway as means against ethanol stress. Upregulation of photosynthesis by ethanol

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was also further confirmed at transcriptional level (Wang et al., 2012b). Based on proteomic and transcriptomic analyses, a list of potential gene targets was generated, which could be used for further engineering ethanol tolerance in Synechocystis sp.

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PCC 6803.

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Butanol tolerance: Compared with ethanol, butanol has many advantages such as higher energy density, lower volatility and corrosiveness, better blending ability and

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compatibility with existing fuel transportation and storage infrastructure, which make

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it a better gasoline substitute (Dürre, 2007). Several recent studies showed that

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butanol could be produced in engineered cyanobacteria systems. Introduction of an artificial isobutanol biosynthetic pathway into S. elongatus PCC 7942 resulted in 1100

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mg/L isobutyraldehyde and 450 mg/L isobutanol production, respectively (Atsumi et al., 2009). Further efforts by artificially engineering ATP consumption through a pathway modification can drive the thermodynamically unfavorable condensation of two molecules of acetyl-CoA to acetoacetyl-CoA forward and enable the direct photosynthetic production of 1-butanol from cyanobacteria S. elongatus PCC 7942. In addition, by replace the bifunctional aldehyde/alcohol dehydrogenase (AdhE2) with separate butyraldehyde dehydrogenase (Bldh) and NADPH-dependent alcohol dehydrogenase (YqhD) further increased 1-butanol production by 4-fold. Finally, the recombinant cyanobacteria strain achieved a production level of 29.9 mg/L 1-butanol

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ACCEPTED MANUSCRIPT (Lan and Liao, 2012b). Cyanobacteria are sensitive to butanol toxicity. The tolerance level of

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Synechocystis sp. PCC 6803 to butanol was found to be about 10 times lower than

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other microbes ever being investigated, including E. coli, Z. mobilis, P. putide, C. acetobutylicum and yeast, whose tolerance levels are typically around 1.5-2.0% (Tian et al., 2012). To build a foundation necessary to engineer robust butanol-producing

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cyanobacterial hosts, Tian et al. (2013) investigated the proteomic changes caused by

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butanol exposure in Synechocystis sp. PCC 6803 cells by quantitative iTRAQ LC-MS/MS proteomic technology, and identified that 303 proteins were regulated

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differentially among the total of 1452 proteins detected. The results indicated that

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butanol exposure led to the decreased overall primary metabolism and the increased

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specific responses for combating stress, such as induction of heat shock protein and transporters, modification of cell membrane and envelope, and initiation of oxidative

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stress response. Significant abundance changes in proteins involved in transport and membrane/envelope modification functions suggested that they could be the major responses during the butanol treatment (Tian et al., 2012). Zhu et al. (2013) applied quantitative RNA-seq transcriptomic and metabolomic approaches to determine the transcriptional and metabolite changes upon butanol stress in Synechocystis sp. PCC 6803. The results showed that genes encoding heat shock proteins, oxidative stress related proteins, transporters and proteins involved in common stress responses, were induced, and 46 out of 73 chemically classified metabolites were differentially regulated by butanol exposure. Notably, 3-phosphoglycerate, glycine, serine and urea

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ACCEPTED MANUSCRIPT related to general stress responses were elevated in butanol-treated cells. In addition, gene knockout mutants and comparative growth analysis validated that three gene

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targets identified from the integrated “omics” analysis, sll0690 encoding a probable

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transcription regulator, slr0947 encoding an OmpR-type DNA-binding response regulator, and slr1295 encoding an iron transport system substrate-binding protein were involved in butanol resistance (Zhu et al., 2013). In a recent study, Anfelt et al. used RNA-Seq analysis to assess the transcriptome response of

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(2013) also

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Synechocystis sp. PCC 6803 to two concentrations of exogenous n-butanol. Approximately 80 transcripts were differentially expressed at 40 mg/L butanol, and

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280 transcripts were different at 1 g/L butanol. Based on the physiology and

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transcriptomics data, the researchers selected several genes for overexpression in an

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attempt to improve butanol tolerance and found that overexpression of several genes, including the small heat shock protein encoding gene hspA (sll1514), ferredoxin

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encoding gene fdxIII (slr1828), superoxide dismutase encoding gene sodB (slr1516) and ssr0692 encoding a hypothetical protein can improve tolerance to butanol (Anfelt et al., 2013).

Alkane tolerance: Alkanes are the major constituents of gasoline and diesel. Although industry-scale production of alkanes through microbiological approach has not been established, it is known that a diversity of microorganisms including some cyanobacteria species can produce low-concentration alkanes in their native forms (Dembitsky and Srebnik, 2002; Schirmer et al., 2010; Winters et al., 1969). The biosynthetic pathway of alkanes was recently constructed using genes from

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ACCEPTED MANUSCRIPT cyanobacterial sources. In one study, Schirmer et al. (2010) constructed a pathway consisting of an acyl–acyl carrier protein reductase and an aldehyde decarbonylase,

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which together converted intermediates of fatty acid metabolism to alkanes and

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alkenes, and the final titer of C13 to C17 mixtures of alkanes and alkenes reached 0.3 g/L when the alkane operon was expressed in E. coli (Schirmer et al., 2010). Through a heterologous expression of the acyl-ACP reductase and aldehyde decarbonylase

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genes from S. elongatus PCC 7942 in Synechococcus sp. PCC7002 that produces no

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alkane in its native form, the researchers also achieved the intracellular accumulation of n-alkane up to 5% of the dry cell weight in Synechococcus sp. PCC7002 (Reppas

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and Ridley, 2010).

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To overcome the low tolerance to alkanes in cyanobacteria, Liu et al. (2012)

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applied a quantitative proteomic approach with iTRAQ - LC-MS/MS technologies to investigate the responses of the model cyanobacterial Synechocystis PCC 6803 to 0.8%

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(v/v) hexane, a representative of alkane. Functional annotation and KEGG pathway enrichment analyses showed that common stress responses were induced by hexane in Synechocystis. Notably, a large number of transporters and membrane-bound proteins, proteins against oxidative stress and proteins related to sulfur relay system and photosynthesis were induced, suggesting that they are possibly the major protection mechanisms against hexane toxicity (Liu et al., 2012).

5. Conclusion To establish high-efficiency biofuel-producing systems in various non-native

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ACCEPTED MANUSCRIPT producing microorganisms, one of the major hurdles needs to be overcome is the low tolerance of these microorganisms to the toxic biofuels. In recent years, efforts have

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been made in: i) applying systems biology tools to determine the global responses of

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non-native biofuel-producing cells to the exogenous biofuels and to decipher molecular mechanisms related to biofuel tolerance, and ii) engineering high-tolerance against biofuels using synthetic biology strategies. Significant progresses have been

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made in several non-native biofuel-producing microbes, such as the best-characterized

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E. coli systems, the Lactobacillus systems with relatively high biofuel tolerance, and the photosynthetic cyanobacterial systems that can be used to produce the

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third-generation carbon-neutral biofuels. These progresses provided evidences that

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engineering more robust non-native microbial systems could be a good way to

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enhance biofuel productivity, and the studies will eventually contribute to the economically feasible operation of large-scale production of biofuels in non-native

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microbial systems in the future. Meanwhile, recent studies also showed that the microbial cells tend to employ a combination of multiple cellular changes to achieve full protection against biofuel toxicity, while so far most of genetic engineering works involved modification of only a limited number of genes/proteins. With the rapid advances in methodologies and fundamentals of synthetic biology (Kim et al., 2013; Lee et al., 2013), it is fully expected that a large-scale engineering of genes, proteins or genetic circuits across multiple cellular functions will allow greater improvement of biofuel tolerance in these microorganisms.

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ACCEPTED MANUSCRIPT Acknowledgements The research was supported by grants from National Basic Research Program of

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China (“973” program, project No. 2011CBA00803, No. 2012CB721101 and

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2014CB745101), National High-tech R&D Program (“863” program, project No. 2012AA02A707), and the Tianjin Municipal Science and Technology Commission (project No. 12HZGJHZ01000). The authors would also like to thank Tianjin

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in establishing the research laboratory.

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University and the “985 Project” of Ministry of Education for their generous supports

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Figure 1: Up-regulated genes/proteins related to photosynthesis in ethanol-treated Synechocystis sp. PCC 6803 cell. The up-regulated genes/proteins associated with

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each of the systems in photosynthesis were highlighted in red. PE: phycoerythrin, PC: plastocyanin, AP: allophycocyanin, FNR: ferredoxin-NADP reductase.

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