Hydroxylation and Further Oxidation of Δ9-Tetrahydrocannabinol by Alkane-Degrading Bacteria

The microbial biotransformation of Δ⁹-tetrahydrocannabinol was investigated using a collection of 206 alkane-degrading strains. Fifteen percent of these strains, mainly gram-positive strains from the genera Rhodococcus, Mycobacterium, Gordonia, and Dietzia, yielded more-polar derivatives. Eight derivatives were produced on a mg scale, isolated, and purified, and their chemical structures were elucidated with the use of liquid chromatography-mass spectrometry, ¹H-nuclear magnetic resonance (¹H-NMR), and two-dimensional NMR (¹H-¹H correlation spectroscopy and heteronuclear multiple bond coherence). All eight biotransformation products possessed modified alkyl chains, with hydroxy, carboxy, and ester functionalities. In a number of strains, β-oxidation of the initially formed C₅ carboxylic acid led to the formation of a carboxylic acid lacking two methylene groups.Δ⁹-Tetrahydrocannabinol (Δ⁹-THC) is the decarboxylated product of the corresponding Δ⁹-THC acid, the major cannabinoid present in the cannabis plant (Cannabis sativa L., Cannabaceae). This compound is officially registered as a drug for the stimulation of appetite and antiemesis in patients under chemotherapy and human immunodeficiency virus therapy regimens. Other biological activities ascribed to this compound include lowering intraocular pressure in glaucoma, acting as an analgesic for muscle relaxation, immunosuppression, sedation, bronchodilation, and neuroprotection (11).Δ⁹-THC and many of its derivatives are highly lipophilic and poorly water soluble. Calculations of the n-octanol/water partition coefficient (K_o/w) of Δ⁹-THC at neutral pH vary between 6,000, using the shake flask method (15), and 9.44 × 10⁶, by reverse-phase high-performance liquid chromatography estimation (19). The poor water solubility and high lipophilicity of cannabinoids cause their absorption across the lipid bilayer membranes and fast elimination from blood circulation. In terms of the “Lipinsky rule of 5” (14), the high lipophilicity of cannabinoids hinders the further development of these compounds into large-scale pharmaceutical products.To generate more water-soluble analogues, one can either apply de novo chemical synthesis (as, e.g., in reference 16) or modify naturally occurring cannabinoids, e.g., by introducing hydroxy, carbonyl, or carboxy groups. Chemical hydroxylation of compounds such as cannabinoids is difficult (Δ⁹-THC is easily converted into Δ⁸-THC under mild conditions), and therefore microbial biotransformation of cannabinoids is potentially a more fruitful option to achieve this goal.So far, studies on biotransformation of Δ⁹-THC were mainly focused on fungi, which led to the formation of a number of mono- and dihydroxylated derivatives. Previous reports on the biotransformation of cannabinoids by various microorganisms are summarized in Table ​Table1.1. The aim of the present study was to test whether bacterial strains are capable of transforming Δ⁹-THC into new products (with potentially better pharmaceutical characteristics) at a higher yield and specificity than previously found for fungal strains. For this purpose, we have chosen to use a collection of alkane-degrading strains, since it was shown in previous studies (8, 18, 20) that alkane oxygenases often display a broad substrate range. Production of novel cannabinoid derivatives that might have interesting pharmacological activities was another objective of this project.

TABLE 1.

Previous biotransformation experiments conducted using various microorganisms to transform cannabinoids

Adaptive Divergence in Experimental Populations of Pseudomonas fluorescens. IV. Genetic Constraints Guide Evolutionary Trajectories in a Parallel Adaptive Radiation

The capacity for phenotypic evolution is dependent upon complex webs of functional interactions that connect genotype and phenotype. Wrinkly spreader (WS) genotypes arise repeatedly during the course of a model Pseudomonas adaptive radiation. Previous work showed that the evolution of WS variation was explained in part by spontaneous mutations in wspF, a component of the Wsp-signaling module, but also drew attention to the existence of unknown mutational causes. Here, we identify two new mutational pathways (Aws and Mws) that allow realization of the WS phenotype: in common with the Wsp module these pathways contain a di-guanylate cyclase-encoding gene subject to negative regulation. Together, mutations in the Wsp, Aws, and Mws regulatory modules account for the spectrum of WS phenotype-generating mutations found among a collection of 26 spontaneously arising WS genotypes obtained from independent adaptive radiations. Despite a large number of potential mutational pathways, the repeated discovery of mutations in a small number of loci (parallel evolution) prompted the construction of an ancestral genotype devoid of known (Wsp, Aws, and Mws) regulatory modules to see whether the types derived from this genotype could converge upon the WS phenotype via a novel route. Such types—with equivalent fitness effects—did emerge, although they took significantly longer to do so. Together our data provide an explanation for why WS evolution follows a limited number of mutational pathways and show how genetic architecture can bias the molecular variation presented to selection.UNDERSTANDING—and importantly, predicting—phenotypic evolution requires knowledge of the factors that affect the translation of mutation into phenotypic variation—the raw material of adaptive evolution. While much is known about mutation rate (e.g., Drake et al. 1998; Hudson et al. 2002), knowledge of the processes affecting the translation of DNA sequence variation into phenotypic variation is minimal.Advances in knowledge on at least two fronts suggest that progress in understanding the rules governing the generation of phenotypic variation is possible (Stern and Orgogozo 2009). The first stems from increased awareness of the genetic architecture underlying specific adaptive phenotypes and recognition of the fact that the capacity for evolutionary change is likely to be constrained by this architecture (Schlichting and Murren 2004; Hansen 2006). The second is the growing number of reports of parallel evolution (e.g., Pigeon et al. 1997; ffrench-Constant et al. 1998; Allender et al. 2003; Colosimo et al. 2004; Zhong et al. 2004; Boughman et al. 2005; Shindo et al. 2005; Kronforst et al. 2006; Woods et al. 2006; Zhang 2006; Bantinaki et al. 2007; McGregor et al. 2007; Ostrowski et al. 2008)—that is, the independent evolution of similar or identical features in two or more lineages—which suggests the possibility that evolution may follow a limited number of pathways (Schluter 1996). Indeed, giving substance to this idea are studies that show that mutations underlying parallel phenotypic evolution are nonrandomly distributed and typically clustered in homologous genes (Stern and Orgogozo 2008).While the nonrandom distribution of mutations during parallel genetic evolution may reflect constraints due to genetic architecture, some have argued that the primary cause is strong selection (e.g., Wichman et al. 1999; Woods et al. 2006). A means of disentangling the roles of population processes (selection) from genetic architecture is necessary for progress (Maynard Smith et al. 1985; Brakefield 2006); also necessary is insight into precisely how genetic architecture might bias the production of mutations presented to selection.Despite their relative simplicity, microbial populations offer opportunities to advance knowledge. The wrinkly spreader (WS) morphotype is one of many different niche specialist genotypes that emerge when experimental populations of Pseudomonas fluorescens are propagated in spatially structured microcosms (Rainey and Travisano 1998). Previous studies defined, via gene inactivation, the essential phenotypic and genetic traits that define a single WS genotype known as LSWS (Spiers et al. 2002, 2003) (Figure 1). LSWS differs from the ancestral SM genotype by a single nonsynonymous nucleotide change in wspF. Functionally (see Figure 2), WspF is a methyl esterase and negative regulator of the WspR di-guanylate cyclase (DGC) (Goymer et al. 2006) that is responsible for the biosynthesis of c-di-GMP (Malone et al. 2007), the allosteric activator of cellulose synthesis enzymes (Ross et al. 1987). The net effect of the wspF mutation is to promote physiological changes that lead to the formation of a microbial mat at the air–liquid interface of static broth microcosms (Rainey and Rainey 2003).Open in a separate windowFigure 1.—Outline of experimental strategy for elucidation of WS-generating mutations and their subsequent identity and distribution among a collection of independently evolved, spontaneously arising WS genotypes. The strategy involves, first, the genetic analysis of a specific WS genotype (e.g., LSWS) to identify the causal mutation, and second, a survey of DNA sequence variation at specific loci known to harbor causal mutations among a collection of spontaneously arising WS genotypes. For example, suppressor analysis of LSWS using a transposon to inactivate genes necessary for expression of the wrinkly morphology delivered a large number of candidate genes (top left) (Spiers et al. 2002). Genetic and functional analysis of these candidate genes (e.g., Goymer et al. 2006) led eventually to the identity of the spontaneous mutation (in wspF) responsible for the evolution of LSWS from the ancestral SM genotype (Bantinaki et al. 2007). Subsequent analysis of the wspF sequence among 26 independent WS genotypes (bottom) showed that 50% harbored spontaneous mutations (of different kinds; see Open in a separate windowFigure 2.—Network diagram of DGC-encoding pathways underpinning the evolution of the WS phenotype and their regulation. Overproduction of c-di-GMP results in overproduction of cellulose and other adhesive factors that determine the WS phenotype. The ancestral SBW25 genome contains 39 putative DGCs, each in principle capable of synthesizing the production of c-di-GMP, and yet WS genotypes arise most commonly as a consequence of mutations in just three DGC-containing pathways: Wsp, Aws, and Mws. In each instance, the causal mutations are most commonly in the negative regulatory component: wspF, awsX, and the phosphodiesterase domain of mwsR (see text).To determine whether spontaneous mutations in wspF are a common cause of the WS phenotype, the nucleotide sequence of this gene was obtained from a collection of 26 spontaneously arising WS genotypes (WS_A-Z) taken from 26 independent adaptive radiations, each founded by the same ancestral SM genotype (Figure 1): 13 contained mutations in wspF (Bantinaki et al. 2007). The existence of additional mutational pathways to WS provided the initial motivation for this study.

TABLE 1

Mutational causes of WS

Elimination of d-Lactate Synthesis Increases Poly(3-Hydroxybutyrate) and Ethanol Synthesis from Glycerol and Affects Cofactor Distribution in Recombinant Escherichia coli

The effect of eliminating d-lactate synthesis in poly(3-hydroxybutyrate) (PHB)-accumulating recombinant Escherichia coli (K24K) was analyzed using glycerol as a substrate. K24KL, an ldhA derivative, produced more biomass and had altered carbon partitioning among the metabolic products, probably due to the increased availability of carbon precursors and reducing power. This resulted in a significant increase of PHB and ethanol synthesis and a decrease in acetate production. Cofactor measurements revealed that cultures of K24K and K24KL had a high intracellular NADPH content and that the NADPH/NADP⁺ ratio was higher than the NADH/NAD⁺ ratio. The ldhA mutation affected cofactor distribution, resulting in a more reduced intracellular state, mainly due to a further increase in NADPH/NADP⁺. In 60-h fed-batch cultures, K24KL reached 41.9 g·liter⁻¹ biomass and accumulated PHB up to 63% ± 1% (wt/wt), with a PHB yield on glycerol of 0.41 ± 0.03 g·g⁻¹, the highest reported using this substrate.Poly(3-hydroxybutyrate) (PHB) is the best-known and most common polyhydroxyalkanoate (PHA). PHAs are polymers with thermoplastic properties that are totally biodegradable by microorganisms present in most environments and that can be produced from different renewable carbon sources (38). Accumulated as intracellular granules by many bacteria under unfavorable conditions (1, 21), PHAs are carbon and energy reserves and also act as electron sinks, enhancing the fitness and stress resistance of bacteria and contributing to redox balance (12, 30). Escherichia coli offers a well-defined physiological environment for the construction and manipulation of various metabolic pathways to produce different bioproducts, such as PHB, from cost-effective carbon sources.In recent years, a significant increase in the production of biodiesel has caused a sharp fall in the cost of glycerol, the main by-product of biodiesel synthesis. As a result, glycerol has become a very attractive substrate for bacterial fermentations (10), specially for reduced products, such as PHB (36). The E. coli strain used in this work, K24K, carries phaBAC, the structural genes responsible for PHB synthesis, from Azotobacter sp. strain FA8 (23) (Table ​(Table1).1). The pha genes in K24K are expressed from a chimeric promoter and consequently are not subject to the genetic regulatory systems present in natural PHA producers. Because of this, it can be assumed that regulation of PHA synthesis in the recombinants is restricted by enzyme activity levels, modulated principally by substrate availability. In most natural producers, and also in PHB-producing E. coli recombinants, PHB is synthesized through the condensation of two molecules of acetyl-coenzyme A (acetyl-CoA), catalyzed by an acetoacetyl-CoA transferase or 3-ketothiolase, resulting in acetoacetyl-CoA. This compound is subsequently reduced by an NAD(P)H-dependent acetoacetyl-CoA reductase to R-(−)-3-hydroxybutyryl-CoA, which is then polymerized by a specific PHA synthase (34).

TABLE 1.

E. coli strains, plasmids, and oligonucleotides used in this study

Antimicrobial Activity of Simulated Solar Disinfection against Bacterial,Fungal, and Protozoan Pathogens and Its Enhancement by Riboflavin

Riboflavin significantly enhanced the efficacy of simulated solar disinfection (SODIS) at 150 watts per square meter (W m⁻²) against a variety of microorganisms, including Escherichia coli, Fusarium solani, Candida albicans, and Acanthamoeba polyphaga trophozoites (>3 to 4 log₁₀ after 2 to 6 h; P < 0.001). With A. polyphaga cysts, the kill (3.5 log₁₀ after 6 h) was obtained only in the presence of riboflavin and 250 W m⁻² irradiance.Solar disinfection (SODIS) is an established and proven technique for the generation of safer drinking water (11). Water is collected into transparent plastic polyethylene terephthalate (PET) bottles and placed in direct sunlight for 6 to 8 h prior to consumption (14). The application of SODIS has been shown to be a simple and cost-effective method for reducing the incidence of gastrointestinal infection in communities where potable water is not available (2-4). Under laboratory conditions using simulated sunlight, SODIS has been shown to inactivate pathogenic bacteria, fungi, viruses, and protozoa (6, 12, 15). Although SODIS is not fully understood, it is believed to achieve microbial killing through a combination of DNA-damaging effects of ultraviolet (UV) radiation and thermal inactivation from solar heating (21).The combination of UVA radiation and riboflavin (vitamin B₂) has recently been reported to have therapeutic application in the treatment of bacterial and fungal ocular pathogens (13, 17) and has also been proposed as a method for decontaminating donor blood products prior to transfusion (1). In the present study, we report that the addition of riboflavin significantly enhances the disinfectant efficacy of simulated SODIS against bacterial, fungal, and protozoan pathogens.Chemicals and media were obtained from Sigma (Dorset, United Kingdom), Oxoid (Basingstoke, United Kingdom), and BD (Oxford, United Kingdom). Pseudomonas aeruginosa (ATCC 9027), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), and Fusarium solani (ATCC 36031) were obtained from ATCC (through LGC Standards, United Kingdom). Escherichia coli (JM101) was obtained in house, and the Legionella pneumophila strain used was a recent environmental isolate.B. subtilis spores were produced from culture on a previously published defined sporulation medium (19). L. pneumophila was grown on buffered charcoal-yeast extract agar (5). All other bacteria were cultured on tryptone soy agar, and C. albicans was cultured on Sabouraud dextrose agar as described previously (9). Fusarium solani was cultured on potato dextrose agar, and conidia were prepared as reported previously (7). Acanthamoeba polyphaga (Ros) was isolated from an unpublished keratitis case at Moorfields Eye Hospital, London, United Kingdom, in 1991. Trophozoites were maintained and cysts prepared as described previously (8, 18).Assays were conducted in transparent 12-well tissue culture microtiter plates with UV-transparent lids (Helena Biosciences, United Kingdom). Test organisms (1 × 10⁶/ml) were suspended in 3 ml of one-quarter-strength Ringer''s solution or natural freshwater (as pretreated water from a reservoir in United Kingdom) with or without riboflavin (250 μM). The plates were exposed to simulated sunlight at an optical output irradiance of 150 watts per square meter (W m⁻²) delivered from an HPR125 W quartz mercury arc lamp (Philips, Guildford, United Kingdom). Optical irradiances were measured using a calibrated broadband optical power meter (Melles Griot, Netherlands). Test plates were maintained at 30°C by partial submersion in a water bath.At timed intervals for bacteria and fungi, the aliquots were plated out by using a WASP spiral plater and colonies subsequently counted by using a ProtoCOL automated colony counter (Don Whitley, West Yorkshire, United Kingdom). Acanthamoeba trophozoite and cyst viabilities were determined as described previously (6). Statistical analysis was performed using a one-way analysis of variance (ANOVA) of data from triplicate experiments via the InStat statistical software package (GraphPad, La Jolla, CA).The efficacies of simulated sunlight at an optical output irradiance of 150 W m⁻² alone (SODIS) and in the presence of 250 μM riboflavin (SODIS-R) against the test organisms are shown in Table ​Table1.1. With the exception of B. subtilis spores and A. polyphaga cysts, SODIS-R resulted in a significant increase in microbial killing compared to SODIS alone (P < 0.001). In most instances, SODIS-R achieved total inactivation by 2 h, compared to 6 h for SODIS alone (Table ​(Table1).1). For F. solani, C. albicans, ands A. polyphaga trophozoites, only SODIS-R achieved a complete organism kill after 4 to 6 h (P < 0.001). All control experiments in which the experiments were protected from the light source showed no reduction in organism viability over the time course (results not shown).

TABLE 1.

Efficacies of simulated SODIS for 6 h alone and with 250 μM riboflavin (SODIS-R)

Alleviation of Proteolytic Sensitivity To Enhance Recombinant Lipase Production in Escherichia coli

Two amino acids, Leu149 and Val223, were identified as proteolytically sensitive when Pseudozyma antarctica lipase (PalB) was heterologously expressed in Escherichia coli. The functional expression was enhanced using the double mutant for cultivation. However, the recombinant protein production was still limited by PalB misfolding, which was resolved by DsbA coexpression.Though Escherichia coli retains popularity as a host for recombinant protein production, it has technical limitations for expressing eukaryotic proteins. Host/protein incompatibility is critical, since eukaryotic proteins heterologously expressed in E. coli are recognized as a foreign object that can induce heat shock responses and drive protease-mediated degradation. E. coli contains several proteases situated in various intracellular compartments, including the cytoplasm, periplasm, inner membrane, and outer membrane (7, 9). While these proteases play a pivotal role in maintaining cell physiology by clearing up abnormal proteins (4), they can potentially degrade recombinant proteins (6). Nevertheless, the mechanisms associated with protein degradation and protein substrate specificity are incompletely understood.Since the proteolysis of recombinant proteins is a common issue, approaches to overcome this limitation have been extensively explored. These include using protease-deficient mutants as an expression host (10, 18), lowering the cultivation temperature (3), coexpressing folding factors (19, 20), applying protein fusion technology (2, 8), eliminating protease cleavage sites (5, 15), and modifying target protein hydrophobicity (11). While genetic elimination of proteolytically sensitive sequences without impacting the target protein''s bioactivity appears to be technically attractive, there is no effective prediction or identification of potential protease cleavage sites. Proteolytically sensitive sequences might not be specific to certain proteases. Various factors affecting the folding, solubility, steric hindrance, and binding of the substrate protein, e.g., neighboring domains or amino acids, can contribute to the sensitivity of proteolytic sites, making sequence manipulation for proteolysis alleviation more difficult.Herein, the recombinant protein''s sensitivity toward intracellular proteolysis was genetically alleviated to enhance the functional expression of PalB, an industrial enzyme with justified applications (1), in E. coli and to understand the relationship between proteolytic specificity and substrate protein sequence. Since there are three intramolecular disulfide bonds whose formation can potentially affect PalB structure and bioactivity, PalB expression in the oxidative periplasm of E. coli was explored (20, 22). However, the expressed PalB protein was extremely sensitive to intracellular proteolysis, resulting in complete degradation. To overcome this problem, PalB mutant variants that were stable against proteolysis were derived (Table ​(Table11).

TABLE 1.

Strains, plasmids, and oligonucleotides