Improved Squalene Production via Modulation of the Methylerythritol 4-Phosphate Pathway and Heterologous Expression of Genes from Streptomyces peucetius ATCC 27952 in Escherichia coli

Putative hopanoid genes from Streptomyces peucetius were introduced into Escherichia coli to improve the production of squalene, an industrially important compound. High expression of hopA and hopB (encoding squalene/phytoene synthases) together with hopD (encoding farnesyl diphosphate synthase) yielded 4.1 mg/liter of squalene. This level was elevated to 11.8 mg/liter when there was also increased expression of dxs and idi, E. coli genes encoding 1-deoxy-d-xylulose 5-phosphate synthase and isopentenyl diphosphate isomerase.Squalene, an industrially important compound obtained primarily from the liver oil of deep-sea sharks and whales, is an important ingredient in skin cosmetics due to its photoprotective role (2, 7). The decreased cancer risk associated with high olive oil consumption could result from high squalene content (12, 16). Squalene has a chemopreventive effect on colon cancer (14). Moreover, squalene has wide applications in fine chemicals, magnetic tape, and low-temperature lubricants and as an additive in animal feed (1).The use of shark liver oil is limited, due to the presence of environmental pollutants, such as polychlorinated biphenyls, heavy metals, and methylmercury residues, as well as an unpleasant fishy odor and taste (17, 19). Moreover, the presence of similar compounds, such as cholesterol, in the oils from marine animal liver can make squalene purification difficult. In addition, squalene production is limited by uncertain availability because of international concern for the protection of marine animals. Squalene has also been obtained from plant sources (4, 10, 11, 18), but very few methods can produce sufficient quantities at the desired purity level for pharmaceutical and industrial applications (6). The use of engineered microbial cell factories for the biosynthesis of squalene may be a suitable alternative to address these issues.In the genome project for Streptomyces peucetius ATCC 27952, a cluster of genes which comprises five open reading frames, encoding hopanoid biosynthesis, has been detected and annotated. Even though these open reading frames share sequence homology with genes involved in hopanoid biosynthesis, no plausible hopanoid products have been isolated from S. peucetius in all laboratory cultures. Therefore, the hopanoid biosynthetic gene cluster of S. peucetius was considered “cryptic” in the present study. We were interested in activating the so-called “cryptic” hopanoid biosynthetic gene cluster of S. peucetius to produce pharmaceutically important compounds by using genetic engineering tools. Isoprenoid production in Escherichia coli has been extensively studied and reviewed (5, 8, 9, 15, 20, 21), but very few reports detail squalene formation in E. coli by the use of exogenous genes (13). In the present study, we introduced three cryptic genes (hopABD) from the hopanoid biosynthesis gene cluster from S. peucetius that catalyzed squalene production and also modulated the 2-C-methyl-d-erythritol 4-phosphate pathway in E. coli to enhance squalene production (Fig. ​(Fig.11).Open in a separate windowFIG. 1.Schematic representation of the engineered squalene biosynthetic pathway in E. coli BL21(DE3). DXS and IDI were overexpressed for the modulation of the MEP pathway to increase and balance the IPP pool, HopD (farnesyl diphosphate synthase) was overexpressed to increase FPP, and HopA and HopB (HopAB) (squalene synthases) were overexpressed to overproduce squalene. The recombinant enzymes overexpressed in E. coli are boxed.     

Critical Evaluation of the Volumetric “Bottle Effect” on Microbial Batch Growth

We have analyzed the impact of surface-to-volume ratio on final bacterial concentrations after batch growth. We examined six bottle sizes (20 to 1,000 ml) using three independent enumeration methods to quantify growth. We found no evidence of a so-called volumetric bottle effect, thus contradicting numerous previous reports.Microbial batch growth during confined incubation in bottles of various sizes is used daily in a broad variety of microbiological studies and methods, including bioassays such as the assimilable organic carbon (AOC) assay (6, 10, 18) and the analysis of pure culture or microbial community growth in freshwater (3, 11, 19, 20). In this context, “bottle effect” or “volume effect” is a term that has cropped up frequently in aquatic microbiology papers (e.g., references 12, 13, and 21) during the last 100 years to explain inexplicable phenomena and variations in results obtained from such batch growth studies. The uncertainty surrounding this apparent effect was clearly summarized in a recent paper by Pernthaler and Amann (16): “Such investigations are often plagued by the mysterious ‘bottle effect’, a hard-to-define concept that reflects the worry of whether phenomena observed in confined assemblages are nonspecific consequences of the confinement rather than a result of the planned manipulation.” The “bottle effect” alludes to an apparent reaction of bacteria to batchwise incubation in a confined environment, and this concept has intermittently been linked to influences on final cell concentrations (3) and grazing/bacterivory (13), a change in viability/activity parameters (9), a change in cultivability (5), and a change in population composition (1).The fact that microbiological processes during confined incubation differ from those in the environment is indisputable. However, a particular section of “bottle effect” literature focuses specifically on a volumetric “bottle effect”, where the above-mentioned effects are linked specifically to the size (or surface-to-volume ratio) of the incubation vessel (3, 8, 11-13, 15, 21). One of the oldest and best-known studies summarized clearly: “It will be observed that the densest bacterial populations appear in the bottles of water which offer the largest area of glass surface per unit volume of water” (21). This idea has established itself as dogma during the last century, with only a few differing opinions (4). However, precious little empirical data that actually quantify and explain the volumetric “bottle effect” are ever presented. In one example, Bischofberger et al. (3) observed that incubation of groundwater led to significantly more growth (about 2 log units) in small bottles (100 ml) than in big ones (10 liters). More often, however, the “bottle effect” is merely mentioned, as if it is self-explanatory and indisputable (2, 11, 12). In the present study, we took a simple but detailed look at the effect of bottle size on the outcome of short-term (<5-day) batch growth assays and compared the data critically to information in the literature and current opinion on this topic.Three batch growth experiments were conducted to assess the volumetric bottle effect on final cell concentrations after growth into stationary phase. Six different bottle sizes were used, covering the ranges most often reported in “bottle effect” literature. All glassware and Teflon-coated caps were cleaned comprehensively as described elsewhere (6) to remove any traces of organic carbon that might have been present on surfaces. The bottle sizes were as follows (water volumes and surface area-to-volume ratios [square centimeters to milliliters] are respectively included in parentheses): 1,000 ml (900 ml, 0.3:1), 500 ml (400 ml, 0.4:1), 250 ml (200 ml, 0.6:1), 100 ml (90 ml, 0.8:1), 40 ml (35 ml, 1.5:1), and 20 ml (15 ml, 2.4:1). In the first experiment, a sample of natural river water (dissolved organic carbon [DOC], 3.8 mg/liter; AOC, 0.3 mg/liter) from a small oligotrophic stream was obtained, filter sterilized with a 50-kDa dialysis filter (Fresenius Medical Care), and inoculated (at 10³ cells/ml) with a microbial community used for AOC assays (19). In the second experiment, a sample of the effluent (DOC, 1.2 mg/liter; AOC, 0.03 mg/liter; total cell concentration [TCC], 3 × 10⁵ cells/ml) from a granulated active carbon filter situated in a drinking water pilot plant (7) was collected and used directly for the experiment without additional treatment or inoculation. For the third experiment, sterile Luria-Bertani (LB) medium (diluted 1:10,000; DOC, 0.7 mg/liter; AOC, 0.46 mg/liter) was inoculated with Vibrio cholerae O1 (10³ cells/ml) as described previously (19). The water from each experiment was distributed into triplicate flasks of each size and incubated (at 30°C) until stationary phase was reached. Stationary phase was indicated by no significant increase in the TCC (measured after 3, 4, and 5 days) on consecutive days. Samples from all experiments were analyzed (i) for TCCs after being stained with SYBR green I and subjected to flow cytometry (7, 19), (ii) for ATP by using a commercial luciferin-luciferase assay (Promega Corporation) (7), and (iii) for heterotrophic plate counts (HPC) on R2A agar by a pour plate method with incubation at 30°C for 10 days. Possible biofilm growth was checked by applying sonication to selected samples. However, no wall growth in bottles of any size was observed.Growth was observed in all three experiments. The results show the net growth after subtraction of the initial cell/ATP/HPC concentrations from the final concentrations (Fig. ​(Fig.1).1). The proposed concept of the volumetric bottle effect implies that more growth should occur in smaller bottles. All data sets were subjected to regression analysis, and we observed no significant correlation (P < 0.01) between bottle size and final growth in any of the experiments by any of the three independent methods used for quantification. Figure ​Figure1A1A shows the batch growth results for a natural microbial community in prefiltered river water. This experimental setup is reflective of a typical AOC assay (6) or batch cultivation of natural microbial communities (20). Figure ​Figure1B1B shows the results for direct incubation of a treated drinking water sample. This sample and experimental setup were chosen specifically to assess any potential volumetric “bottle effect” on an indigenous microbial community in a biologically stable water sample, where only limited growth is expected. Indeed, the final cell concentration in the sample was only about 25% higher than the original cell concentration. The cultivability (HPC/TCC × 100) at day 0 was 0.4%, and at the end of the experimental period it had increased to 2.5%. This points to increased cultivability as a result of growth during confinement (5), yet it does not relate at all to the size of the incubation vessel. Figure ​Figure1C1C shows the data for V. cholerae grown in sterile LB medium (diluted 1:10,000) to stationary phase. Again, this particular setup is of specific relevance since a recently published paper on the growth of V. cholerae referred directly to the volumetric “bottle effect” to explain rather large differences between growth results from two separate studies (11, 19). The data from Fig. ​Fig.1C1C suggest at least that a “bottle effect” should be ruled out as an interfering factor in this case.Open in a separate windowFIG. 1.Effects of bottle size on bacterial batch growth of a natural microbial community in filter-sterilized surface water (A), growth of bacteria during direct incubation of water from a drinking water treatment plant (B), and batch growth of a V. cholerae pure culture in diluted LB medium (C). Growth (expressed as the net growth) was quantified by flow cytometric total cell counting (circles), total ATP analysis (diamonds), and conventional plating (squares). All data points represent averages of triplicate measurements.The results presented in this study clearly dispute the concept of a volumetric “bottle effect” on the outcome of short-term batch growth assays, be it for pure cultures or natural microbial communities. These findings contradict evidence reported by many other researchers (3, 8, 11-13, 15, 21). Although the volumetric “bottle effect” is often cited as a somewhat mysterious occurrence, it is imperative that clear experimental data are required for the critical appraisal thereof. The main experimental theory behind the phenomenon is that organic carbon adsorbs to clean glass surfaces, thus locally concentrating the carbon and creating more favorable growth conditions (2, 14). This adsorption and the fact that bacteria can utilize such adsorbed carbon have been demonstrated experimentally (14). What has, in our opinion, not been shown conclusively is that these effects can be so dramatic that they would alter the growth of samples to the extent that different sizes of bottles would render different final cell numbers after growth. Since we have not observed any volumetric “bottle effect” in our work, we can only speculate on the possible reasons why this has been observed previously. One explanation may be that glassware contaminated with organic carbon can contribute to the perception of a volumetric “bottle effect,” as large surface-to-volume ratios (found in small bottles) would account for increased contamination compared to that in bottles with smaller ratios. Hence, more additional available carbon would be introduced into smaller bottles, giving rise to higher final cell numbers after growth. In this context, it is essential that a comprehensive glassware-cleaning protocol be followed, including heating to a high temperature (>500°C) and storage away from volatile organics (6). In addition, it is important that such experiments at low carbon concentrations are complemented with the inclusion of correct and sensitive controls to assess potential organic carbon contamination. For example, the use of deionized water as a negative control should be avoided, since the absence of inorganic nutrients is bound to lead to no growth and thus false-negative results (10). A good negative control would be water that is only carbon limited, e.g., bottled drinking water (17). Moreover, the use of multiple tools for analyzing growth, including cultivation-independent methods, is encouraged.In conclusion, we did not observe evidence of a volumetric bottle effect on short-term (<5-day) batch incubations. The findings of this study suggest that reference to the so-called volumetric bottle effect should be considered carefully unless supported by clear experimental data. This study does not dispute the fact that many authors have observed results implying apparent bottle effects during growth studies, but it questions the interpretation and understanding of this concept and the random use of the term “bottle effect” to explain uncertainty in results, specifically in relation to bottle size. Hopefully, these data will assist with experimental setups and comparison of data among different groups and stimulate discussion of and future research on this interesting, but slightly controversial, topic.     

Enhancement of the Diversity of Polyoxins by a Thymine-7-Hydroxylase Homolog outside the Polyoxin Biosynthesis Gene Cluster

Polyoxins consist of 14 structurally variable components which differentiate at three branch sites of the carbon skeleton. Open reading frame (ORF) SAV_4805 of Streptomyces avermitilis, showing similarity to thymine-7-hydroxylase, was proved to enhance the diversity of polyoxins at the C-5 site of the 1-(5′-amino-5′-deoxy-β-d-allofuranuronosyl) pyrimidine moiety.The antifungal nucleoside antibiotic polyoxins synthesized naturally by Streptomyces cacaoi subsp. asoensis (S. cacaoi here) consist of a mixture of at least 14 different compounds called polyoxins A to N (Fig. ​(Fig.1)1) (6, 13, 25). Most of the polyoxins have a common nucleoside skeleton that is attached with variable side groups at three different places (polyoxins C, I, and N have a modified skeleton). Polyoxins are grouped into four different classes according to the identity of the side group R1 attached at C-5 of the 1-(5′-amino-5′-deoxy-β-d-allofuranuronosyl) pyrimidine moiety. Different classes of polyoxins differ markedly in their activity spectra against plant pathogenic fungi (1, 10, 20).Open in a separate windowFIG. 1.Chemical structure of polyoxin complex. Class is determined by R1. The × indicates a different skeleton that does not have this particular residue.It was deduced that the nucleoside moiety originated from the condensation of uridine with phosphoenolpyruvate (PEP) to generate octosyl acid as the intermediate (7, 12, 14). Then, a subsequent oxidative elimination of the two terminal carbons would create the nucleoside moiety (12). The detailed biosynthetic pathway of nucleoside moiety of polyoxins remains obscure. Our previous work showed that heterologous expression of the polyoxin biosynthetic gene cluster pol in Streptomyces lividans TK24 produces only thymine-derived polyoxin H (class III) (5). This prompted us to investigate the origin of a gene(s) related to the structural variation of polyoxins at the R1 site, which could be located outside the polyoxin biosynthetic gene cluster in the native producer.The pyrimidine rings of polyoxins correspond one to one to the intermediates of the thymidine salvage pathway, which was characterized only for some fungi (see Fig. S1 in the supplemental material) (22). In the prime pathway of nucleotide metabolism, dUMP could be converted to dTMP under the catalysis of thymidylate synthase (TS) with tetrahydrofolic acid as a methyl donor while dTMP could not be converted back to dUMP reversibly (4, 17). In the 1970s, Shaffer et al. separated two enzymes, thymine-7-hydroxylase (THase; official name thymine dioxygenase) and isoorotate decarboxylase (IDCase), from fungal sources which showed potential ability to convert thymine to uracil (22). THase is a trifunctional oxygenase and catalyzes three enzymatic reactions: thymine to 5-hydroxymethyluracil, 5-hydroxymethyluracil to 5-formyluracil, and 5-formyluracil to uracil-5-carboxylic acid (also designated isoorotate) (18, 26). IDCase catalyzes the subsequent decarboxylation reaction, and uracil-5-carboxylic acid is converted to uracil in the end (21). This process is catalyzed by THase, and IDCase is the core step of the thymidine salvage pathway in fungi.BLAST analysis results with the amino acid sequence of THase from Rhodotorula glutinis and IDCase from Neurospora crassa as queries in the 25 sequenced Streptomyces strains (5 finished and 20 in process) of the genome database (from NCBI GenBank, accessed 24 July 2010) showed that the THase and IDCase gene homologs are distributed extensively in Streptomyces, such as open reading frame (ORF) SAV_4805 (sharing 27% identity and 45% similarity with the THase gene) from S. avermitilis strain MA4680 and SCO_6305 (sharing 25% identity and 44% similarity with the IDCase gene) from S. coelicolor strain A3(2) (2, 11, 23). The results indicated a potential thymidine salvage pathway in Streptomyces, and the salvage pathway provides alternative nucleoside monophosphates as precursors for polyoxin biosynthesis.     

The Apparent Malate Synthase Activity of Rhodobacter sphaeroides Is Due to Two Paralogous Enzymes, (3S)-Malyl-Coenzyme A (CoA)/β-Methylmalyl-CoA Lyase and (3S)- Malyl-CoA Thioesterase

Assimilation of acetyl coenzyme A (acetyl-CoA) is an essential process in many bacteria that proceeds via the glyoxylate cycle or the ethylmalonyl-CoA pathway. In both assimilation strategies, one of the final products is malate that is formed by the condensation of acetyl-CoA with glyoxylate. In the glyoxylate cycle this reaction is catalyzed by malate synthase, whereas in the ethylmalonyl-CoA pathway the reaction is separated into two proteins: malyl-CoA lyase, a well-known enzyme catalyzing the Claisen condensation of acetyl-CoA with glyoxylate and yielding malyl-CoA, and an unidentified malyl-CoA thioesterase that hydrolyzes malyl-CoA into malate and CoA. In this study the roles of Mcl1 and Mcl2, two malyl-CoA lyase homologs in Rhodobacter sphaeroides, were investigated by gene inactivation and biochemical studies. Mcl1 is a true (3S)-malyl-CoA lyase operating in the ethylmalonyl-CoA pathway. Notably, Mcl1 is a promiscuous enzyme and catalyzes not only the condensation of acetyl-CoA and glyoxylate but also the cleavage of β-methylmalyl-CoA into glyoxylate and propionyl-CoA during acetyl-CoA assimilation. In contrast, Mcl2 was shown to be the sought (3S)-malyl-CoA thioesterase in the ethylmalonyl-CoA pathway, which specifically hydrolyzes (3S)-malyl-CoA but does not use β-methylmalyl-CoA or catalyze a lyase or condensation reaction. The identification of Mcl2 as thioesterase extends the enzyme functions of malyl-CoA lyase homologs that have been known only as “Claisen condensation” enzymes so far. Mcl1 and Mcl2 are both related to malate synthase, an enzyme which catalyzes both a Claisen condensation and thioester hydrolysis reaction.Many organic compounds are initially metabolized to acetyl coenzyme A (acetyl-CoA), at which point they enter the central carbon metabolism. Examples of such growth substrates are C₁ and C₂ compounds (e.g., methanol and ethanol), fatty acids, waxes, esters, alkenes, or (poly)hydroxyalkanoates. The synthesis of all cell constituents from acetyl-CoA requires a specialized pathway for the conversion of this central C₂ unit into other biosynthetic precursor metabolites. This (anaplerotic) process is referred to as acetyl-CoA assimilation, and two very different strategies have been described, i.e., the glyoxylate cycle and the ethylmalonyl-CoA pathway (12, 21) (Fig. ​(Fig.11).Open in a separate windowFIG. 1.Pathways for acetyl-CoA assimilation. (A) Glyoxylate cycle. The key enzymes are isocitrate lyase and malate synthase. (B) Ethylmalonyl-CoA pathway. The unique enzymes of the pathway are crotonyl-CoA carboxylase/reductase, ethylmalonyl-CoA/methylmalonyl-CoA epimerase, (2R)-ethylmalonyl-CoA mutase, (2S)-methylsuccinyl-CoA dehydrogenase, mesaconyl-CoA hydratase, (3S)-malyl-CoA/β-methylmalonyl-CoA lyase, and (3S)-malyl-CoA thioesterase. The enzymes involved in the (apparent) malate synthase reaction(s) are boxed for each pathway.The glyoxylate cycle for acetyl-CoA assimilation is in fact a modified citric acid cycle that converts two molecules of acetyl-CoA to the citric acid cycle intermediate malate (Fig. ​(Fig.1A)1A) (21). In a first reaction sequence, one molecule of acetyl-CoA is converted into glyoxylate due to the combined action of the initial enzymes of the citric acid cycle and isocitrate lyase, the key enzyme of this assimilation strategy. Isocitrate lyase cleaves the citric cycle intermediate isocitrate into succinate and glyoxylate (22). The glyoxylate formed is then condensed in a second step with another molecule of acetyl-CoA to yield malate and free CoA. Because the two decarboxylation reactions of the citric acid cycle are circumvented by this acetyl-CoA assimilation strategy, the glyoxylate cycle is also referred to as the “glyoxylate bypass” or “glyoxylate shunt.”The ethylmalonyl-CoA pathway for acetyl-CoA assimilation replaces the glyoxylate cycle in bacteria that lack isocitrate lyase (1, 12). In this linear pathway, three molecules of acetyl-CoA, one molecule of CO₂, and one molecule of bicarbonate are converted to the citric acid cycle intermediates succinyl-CoA and malate (Fig. ​(Fig.1B).1B). The ethylmalonyl-CoA pathway requires at least seven unique enzymes. Crotonyl-CoA carboxylase/reductase, ethylmalonyl-CoA mutase, and methylsuccinyl-CoA dehydrogenase are considered key enzymes of the pathway, and all three enzymes have been characterized from Rhodobacter sphaeroides (12-14).Although these two acetyl-CoA strategies differ with respect to their reaction sequence, intermediates and overall balance, the glyoxylate cycle and the ethylmalonyl-CoA pathway both require the condensation of acetyl-CoA and glyoxylate to form malate (Fig. ​(Fig.1,1, boxed). In the glyoxylate cycle, this reaction is catalyzed by malate synthase, whereas in the ethylmalonyl-CoA pathway malate synthase is catalyzed by two separate enzymes, malyl-CoA lyase and malyl-CoA thioesterase (7, 26).Malyl-CoA lyases catalyze the reversible condensation of acetyl-CoA and glyoxylate into malyl-CoA and have been purified from Methylobacterium extorquens, Chloroflexus aurantiacus, Aminobacter aminovorans, and Rhodobacter capsulatus; the corresponding genes were identified as mclA (M. extorquens), mcl (C. aurantiacus), and mcl1 (R. capsulatus) (5, 16, 17, 19, 26). Remarkably, these proteins are promiscuous enzymes that also catalyze the (reversible) cleavage of β-methylmalyl-CoA into glyoxylate and propionyl-CoA, and it has been suggested that these enzymes catalyze both reactions in vivo (16, 19, 26). However, in contrast to malyl-CoA lyase, the malyl-CoA thioesterase catalyzing the highly exergonic hydrolysis of the CoA-thioester into malate and free CoA has not been identified so far, and the nature of the enzyme has remained enigmatic (7, 26).For R. sphaeroides, a malyl-CoA lyase homolog has been shown to be upregulated during growth on acetate, and it was proposed that this protein (Mcl1) catalyzes the cleavage of β-methylmalyl-CoA, as well as the condensation of acetyl-CoA and glyoxylate in the ethylmalonyl-CoA pathway (1). Interestingly, R. sphaeroides encodes a second malyl-CoA lyase homolog with 34% amino acid sequence identity to Mcl1. This protein, named Mcl2, was also shown to be upregulated during growth of R. sphaeroides on acetate, but a function could not be assigned so far (1). We therefore addressed the function of both malyl-CoA lyase homologs by gene inactivation and biochemical studies of recombinant Mcl1 and Mcl2. Based on our findings, we confirm here the function of Mcl1 in R. sphaeroides as (3S)-malyl-CoA/β-methylmalyl-CoA lyase and identify its paralog Mcl2 as the long-sought (3S)-malyl-CoA thioesterase.     

Analysis of the Fine-Scale Population Structure of “Candidatus Accumulibacter phosphatis” in Enhanced Biological Phosphorus Removal Sludge,Using Fluorescence In Situ Hybridization and Flow Cytometric Sorting

To investigate the fine-scale diversity of the polyphosphate-accumulating organisms (PAO) “Candidatus Accumulibacter phosphatis” (henceforth referred to as “Ca. Accumulibacter”), two laboratory-scale sequencing batch reactors (SBRs) for enhanced biological phosphorus removal (EBPR) were operated with sodium acetate as the sole carbon source. During SBR operations, activated sludge always contained morphologically different “Ca. Accumulibacter” strains showing typical EBPR performances, as confirmed by the combined technique of fluorescence in situ hybridization (FISH) and microautoradiography (MAR). Fragments of “Ca. Accumulibacter” 16S rRNA genes were retrieved from the sludge. Phylogenetic analyses together with sequences from the GenBank database showed that “Ca. Accumulibacter” 16S rRNA genes of the EBPR sludge were clearly differentiated into four “Ca. Accumulibacter” clades, Acc-SG1, Acc-SG2, Acc-SG3, and Acc-SG4. The specific FISH probes Acc444, Acc184, Acc72, and Acc119 targeting these clades and some helpers and competitors were designed by using the ARB program. Microbial characterization by FISH analysis using specific FISH probes also clearly indicated the presence of different “Ca. Accumulibacter” cell morphotypes. Especially, members of Acc-SG3, targeted by probe Acc72, were coccobacillus-shaped cells with a size of approximately 2 to 3 μm, while members of Acc-SG1, Acc-SG2, and Acc-SG4, targeted by Acc444, Acc184, and Acc119, respectively, were coccus-shaped cells approximately 1 μm in size. Subsequently, cells targeted by each FISH probe were sorted by use of a flow cytometer, and their polyphosphate kinase 1 (ppk1) gene homologs were amplified by using a ppk1-specific PCR primer set for “Ca. Accumulibacter.” The phylogenetic tree based on sequences of the ppk1 gene homologs was basically congruent with that of the 16S rRNA genes, but members of Acc-SG3 with a distinct morphology comprised two different ppk1 genes. These results suggest that “Ca. Accumulibacter” strains may be diverse physiologically and ecologically and represent distinct populations with genetically determined adaptations in EBPR systems.Enhanced biological phosphorus removal (EBPR) has been applied in many wastewater treatment plants to reduce the phosphorus that causes eutrophication in surface waters. EBPR employs polyphosphate-accumulating organisms (PAOs), which are enriched through alternating aerobic-anaerobic cycles (34). Since PAOs are essential for an understanding of EBPR, many candidates have been proposed as potential PAOs, such as Acinetobacter spp. (11), Tetrasphaera spp. (31), Microlunatus phosphovorus (36), Lampropedia spp. (40), and Gram-positive Actinobacteria (24). However, those organisms do not exhibit all of the characteristics of the EBPR biochemistry model. Recently developed culture-independent approaches such as PCR-clone libraries, fluorescence in situ hybridization (FISH), and microautoradiography (MAR) have highlighted an uncultured Rhodocyclus-related bacterium, “Candidatus Accumulibacter phosphatis” (henceforth referred to as “Ca. Accumulibacter”), as one of the most important PAO candidates (2, 5, 16, 22, 23, 27, 28, 47).Numerous studies have sought to investigate uncultured “Ca. Accumulibacter” and have shown the presence of genetically and physiologically different members with a global geographic distribution (3, 9, 22, 27, 39). For example, Kong et al. (22) identified two morphologically different “Ca. Accumulibacter” cells of small cocci and large coccobacilli labeled with PAOmix (PAO462, PAO651, and PAO846) in laboratory-scale EBPR reactors. Additional results showing phenotypic and morphological diversities of “Ca. Accumulibacter” cells also existed with respect to the different roles of denitrifying PAO (DPAO) in the EBPR process (3, 9, 23). Carvalho et al. (3) detected two different morphotypes of “Ca. Accumulibacter” with different nitrate reduction capabilities. The presence of other “Ca. Accumulibacter” strains with 15% genome sequence divergence from the dominant strains in metagenomic analyses is likely to explain these morphological and phenotypic differences (12). McMahon et al. (33) suggested the use of the polyphosphate kinase (ppk) gene, which is involved in the production of polyphosphate, for a finer elucidation of “Ca. Accumulibacter” diversity. He et al. (15) grouped “Ca. Accumulibacter” strains into five distinct clades, designated clades I, IIA, IIB, IIC, and IID, using ppk gene sequence information. Flowers and colleagues (9) previously reported that “Ca. Accumulibacter” cells of clade IA had nitrate reduction activity with phosphorus uptake but that “Ca. Accumulibacter” cells of clade IIA did not.FISH-fluorescence activated cell sorting (FACS) techniques have been used for the separation of specific microbial cells from complex microbial consortia and their metabolic gene analysis (14, 46). For example, Miyauchi et al. (35) sorted PAOmix probe-labeled “Ca. Accumulibacter” cells from EBPR sludge and analyzed their nitrite reductase gene (nirS) diversity. In the current study, we found that four different “Ca. Accumulibacter” clades (Acc-SG1, Acc-SG2, Acc-SG3, and Acc-SG4) were present in the EBPR sludge of laboratory-scale reactors supplied with acetate as the sole carbon source. We analyzed their morphological characteristics and ppk gene sequence information using a suite of FISH and FACS approaches and linked fine-scale phylogenetic diversities of “Ca. Accumulibacter” strains with their morphological characteristics and metabolic genes. This study will be useful for further genetic and physiological studies of different “Ca. Accumulibacter” clades.     

Microbial Diversity of Septic Tank Effluent and a Soil Biomat

Microbial diversity of septic tank effluent (STE) and the biomat that is formed as a result of STE infiltration on soil were characterized by 16S rRNA gene sequence analysis. Results indicate that microbial communities are different within control soil, STE, and the biomat and that microbes found in STE are not found in the biomat. The development of a stable soil biomat appears to provide the best on-site water treatment or protection for subsequent groundwater interactions of STE.On-site wastewater treatment systems serve approximately 22 million homes throughout the United States (39), resulting in ∼15 billion liters of wastewater, typically treated in septic tanks (Fig. ​(Fig.1A),1A), being discharged into the environment daily (8). Septic tank effluent (STE) is normally discharged into subsurface trenches or beds (i.e., soil treatment units [STU]) (40), where many pathogenic bacteria, viruses, and nutrients are removed, transformed, or destroyed.Open in a separate windowFIG. 1.Shown are typical on-site wastewater system components (A), a chamber system with an open infiltrative architecture (B), and a stone-and-pipe system with a gravel-laden infiltrative surface architecture (C). (Adapted with permission from Infiltrator Systems, Inc.)Within the STU, a complex ecosystem referred to as a biomat evolves over time at and near the soil infiltrative surface in response to STE application (5, 6, 32). This region (1 to 2 cm in thickness) becomes dark in color and has high organic matter accumulation, high water content, and high microbial densities. The biomat may be important from a purification perspective (42); however, excessive soil pore clogging can be detrimental to long-term hydraulic functioning.Biomat formation and potential soil clogging appear to be dependent on several factors: wastewater composition and loading rate (18, 31, 32, 38), soil characteristics (23), microorganisms (2, 11, 14, 24, 29, 33), temperature (17), and wastewater application method (17). Although it is believed that microorganisms are involved, research examining the microbial community of the biomat is limited and until recently has focused only on using plating techniques to determine bacterial numbers (27, 29). Few researchers have attempted to characterize the microbial community found in the biomat (3, 29, 41). In this study, traditional culturing techniques and a molecular approach (see “Methods” in the supplemental material) were used to explore the diversity of microbes found in domestic STE and the biomat that developed in the STU in a sandy loam soil.The biomat that developed within an Ascalon sandy loam soil as a result of STE infiltration over a period of 30 months was characterized using 16S rRNA gene sequence analysis and culturing techniques (37). The microbial communities were analyzed by using STE and biomat samples from two different pilot-scale infiltration units for STE; one (MP10) had an open architecture above the soil infiltrative surface (Fig. ​(Fig.1B),1B), and one (MP9) had gravel aggregate sitting on the soil infiltrative surface (Fig. ​(Fig.1C).1C). For use as a negative control, samples of sandy loam soil were also collected from an infiltration unit at the same site that received clean tap water and had an open architecture. Biomat samples were taken at two depth intervals, 0.0 to 0.5 cm and 0.5 to 1.0 cm from test units MP10 and MP9, and the control sample was taken from 0.0 to 0.5 cm. At the time of sampling, the three infiltration units had received STE or tap water for 30 months.A total of 447 bacterial 16S rRNA gene sequences were generated from samples of the STE and the biomat (two STE units and a tap water unit). This number likely represents a great undersampling of these environments; however, these sequences are sufficient to provide insight into the microbial community phylotype composition. Although “universal” (i.e., all three phylogenetic domains amplified) PCR primers 515F and 1391R (19) were used, only organisms from the bacterial domain were detected. As in a previous study of a biomat (3) and other studies of soil microbial communities (9, 28), Proteobacteria sequences dominated the biomat samples, but Bacteroidetes and Acidobacteria sequences were also found in significant abundance (Fig. ​(Fig.2).2). The control community was comprised mainly of sequences from Proteobacteria, Acidobacteria, and Actinobacteria, with a distribution similar to that of the biomat. However, only 31% of sequences at the family level were shared between the 0.0- to 0.5-cm-depth samples of each biomat and the control. Furthermore, 95% of the operational taxonomic units (OTUs) found in the control sample were not found in any other sample analyzed in this study.Open in a separate windowFIG. 2.Bacterial phylum diversity based on rRNA gene clone libraries and the Ribosomal Database Project classification (7). MP9A, gravel-laden architecture test unit (0.5 cm); MP9B, gravel-laden architecture test unit (1.0 cm); MP10A, open architecture test unit (0.5 cm); MP10B, open architecture test unit (1.0 cm); STE; Control, negative control infiltrative surface architecture; and Summary, a compilation of the sequences of all clones used in this study and examined in all environments. Percentages are based on the total number of clones within each sample.The lack of shared sequences suggests that the nutrient-rich STE fosters the growth of a different soil microbial community. The composition of the effluent applied (clean water versus STE) appears to lead to distinct microbial communities, based on the relatively low percentage of shared OTUs. Additionally, scanning electron micrographs of both biomat and control soil samples were strikingly different, supporting the differences observed by molecular comparative methods (see Fig. S1 in the supplemental material).The STE library was also dominated by proteobacteria (81%), but the class distribution differed considerably from both the control and biomat (see Fig. S2 in the supplemental material). Epsilonproteobacteria (from the genera Sulfurospirillum, Arcobacter, and Sulfurimonas) species represented the dominant subphyla in the STE sample but were absent from all other samples. None of the OTUs found in STE were found in the biomat samples, suggesting that the microbial community of the biomat originates in the soil rather than from the influx of organisms entering the soil in STE. This also may indicate limited survival or the possibility that they are outcompeted by indigenous soil microbes. Species of both the Sulfurospirillum and Sulfurimonas genera have also been found in aquatic environments (13, 16) and contaminated sediments (22). Sequences of Arcobacter spp., aerotolerant gram-negative spiral-shaped bacteria, were the most dominant found in STE. Arcobacter spp. have been found in mangrove sediments (21) and activated sludge (34) and have been associated with human and animal diarrhea (1, 20, 36). The lack of Arcobacter spp. in any of the biomat samples indicates a rapid die-off or predation at the soil infiltrative surface or the possibility that they are vastly outnumbered in this environment and were not detected by the sequencing performed.There was far less overall phylogenetic diversity in STE than in the biomat samples (see Table S1 in the supplemental material). The phylum distribution in the STE is similar to that of the human gut, which contains some of the highest cell densities of any ecosystem (43); however, diversity at the phylum level is among the lowest (15). Studies have shown that the human gut and feces are dominated by Bacteroidetes (30%) and Firmicutes (30%) species (4, 10). The lack of sequences grouping with Firmicutes spp. in this study suggests that they may not survive the septic tank environment. Not surprisingly, Escherichia coli sequences were not detected in this study, as these bacteria represent less than 0.1% of the species found in the colon (10, 35).The amount of fecal coliforms and E. coli bacteria was reduced by a minimum of 90% and 85%, respectively, from the STE to the biomat. Similar to results of previous studies (12, 25, 26, 30), culturable heterotrophic bacteria, fecal coliforms, and E. coli bacteria decreased with the increase in depth (1 to 10 cm) in both of the STE test units. The number of heterotrophic bacteria was 3 to 5 orders of magnitude greater in all samples than counts for fecal coliforms and E. coli. At all depths, the number of fecal coliforms and E. coli were greater in test unit MP10 than in MP9; this may be due in part to differences between open versus gravel-laden infiltration surfaces, with the gravel architecture of MP9 being more conducive to the formation of a water-treating biomat.Further analysis may determine the roles that microbes play in the treatment of organic and inorganic pollutants in the biomat. Ultimately, understanding the microbial community will allow engineers to implement on-site systems that control the rate of biomat formation and thus keep clogging and subsequent failure to a minimum. This improved design and operation would help to protect the underlying groundwater.     

A Novel Dehalobacter Species Is Involved in Extensive 4,5,6,7-Tetrachlorophthalide Dechlorination

The purpose of this study was the enrichment and phylogenetic identification of bacteria that dechlorinate 4,5,6,7-tetrachlorophthalide (commercially designated “fthalide”), an effective fungicide for rice blast disease. Sequential transfer culture of a paddy soil with lactate and fthalide produced a soil-free enrichment culture (designated the “KFL culture”) that dechlorinated fthalide by using hydrogen, which is produced from lactate. Phylogenetic analysis based on 16S rRNA genes revealed the dominance of two novel phylotypes of the genus Dehalobacter (FTH1 and FTH2) in the KFL culture. FTH1 and FTH2 disappeared during culture transfer in medium without fthalide and increased in abundance with the dechlorination of fthalide, indicating their growth dependence on the dechlorination of fthalide. Dehalobacter restrictus TEA is their closest relative, with 97.5% and 97.3% 16S rRNA gene similarities to FTH1 and FTH2, respectively.4,5,6,7-Tetrachlorophthalide (commercially designated “fthalide”) is an effective fungicide for rice blast disease, which inhibits melanin biosynthesis and the formation of the mature appressorial cells of the rice blast pathogen on the host plant (5, 16). Fthalide has been reported to be reductively dechlorinated in soil (16) and compost (28), although its fates in paddy soil and the fthalide-dechlorinating bacteria are unknown. Besides fthalide, polychlorinated aromatic compounds are known to be reductively dechlorinated by the bacteria of several phyla. Six strains of Desulfitobacterium spp. of the phylum Firmicutes (2, 3, 6, 10, 23, 29) and Desulfomonile tiedjei DCB-1 of the phylum Proteobacteria (21) can dechlorinate polychlorinated phenols. Three strains of the phylum Chloroflexi can dechlorinate a variety of compounds, including polychlorinated phenols, benzenes, biphenyls, or dibenzo-p-dioxins: Dehalococcoides ethenogenes 195 (9, 19), Dehalococcoides sp. strain CBDB1 (1, 4), and strain DF-1 of Chloroflexi, collectively called the “o-17/DF-1 group” (18). Dehalococcoides spp. utilize hydrogen as an electron donor and acetate as a carbon source for growth coupled to the reductive dechlorination of chlorinated compounds (1, 12, 13, 19, 26). In contrast, Desulfitobacterium spp. can dechlorinate chlorinated compounds not only with hydrogen, but also organic acids, such as formate, pyruvate, lactate, or butyrate (3, 10, 23). Strain DF-1 can utilize hydrogen and formate for the dechlorination of polychlorinated biphenyls (PCBs) (18).In this study, bacteria that dechlorinate fthalide were enriched from a paddy soil with sequentially transferred cultures using a soil-free medium supplemented with single organic acids. Acetate, formate, lactate, and butyrate were used in this study because they are frequently used in the enrichment of dechlorinators and release hydrogen at different concentrations (8, 11, 14). Fthalide-dechlorinating bacteria in the enriched culture were phylogenetically identified based on the 16S rRNA gene with PCR-denaturing gradient gel electrophoresis (DGGE), a 16S rRNA gene clone library, and quantitative real-time PCR (qPCR).     

Base Flipping in V(D)J Recombination: Insights into the Mechanism of Hairpin Formation,the 12/23 Rule,and the Coordination of Double-Strand Breaks

Tn5 transposase cleaves the transposon end using a hairpin intermediate on the transposon end. This involves a flipped base that is stacked against a tryptophan residue in the protein. However, many other members of the cut-and-paste transposase family, including the RAG1 protein, produce a hairpin on the flanking DNA. We have investigated the reversed polarity of the reaction for RAG recombination. Although the RAG proteins appear to employ a base-flipping mechanism using aromatic residues, the putatively flipped base is not at the expected location and does not appear to stack against any of the said aromatic residues. We propose an alternative model in which a flipped base is accommodated in a nonspecific pocket or cleft within the recombinase. This is consistent with the location of the flipped base at position −1 in the coding flank, which can be occupied by purine or pyrimidine bases that would be difficult to stabilize using a single, highly specific, interaction. Finally, during this work we noticed that the putative base-flipping events on either side of the 12/23 recombination signal sequence paired complex are coupled to the nicking steps and serve to coordinate the double-strand breaks on either side of the complex.Antibody and T-cell receptor (TCR) diversity is generated by V(D)J recombination initiated by the RAG proteins, RAG1 and RAG2. The recombination signal sequences (RSSs), where recombination takes place, have a distinctive arrangement resembling transposon ends. The relationship between V(D)J recombination and transposition was established beyond doubt by the discovery of RAG-mediated transposition and by the identification of a triad of conserved active-site residues. This evidence placed RAG1 firmly within the family of transposases and retroviral integrases that have a characteristic DDE triad of amino acid residues that coordinate catalytic metal ions in the active site (1, 26, 30, 35, 39, 46). Later, the Transib family of transposons was identified as the likely ancestral group of RAG1 (33).In V(D)J recombination, the RAG proteins excise the DNA between a pair of RSSs. This fragment is the equivalent of an excised transposon, and it takes no further part in the canonical V(D)J recombination reaction. Instead, the variable regions of the genes encoding antibodies and TCR are created by the imprecise rejoining of the flanking DNA, referred to as the “coding flank.” A key feature of the cleaved coding flanks is that they have covalently closed hairpin ends. The asymmetric resolution of these hairpins contributes to the diversification of the coding sequences during rejoining. The hairpins themselves arise as a consequence of the molecular mechanism RAG-mediated RSS cleavage.The crystal structure for the catalytic core of the human immunodeficiency virus type 1 integrase protein revealed a structural fold shared in common with RNase H and the Holliday junction resolving enzyme RuvC (22). RNase H and RuvC monomers each perform a simple nicking reaction that requires a single phosphoryl transfer event. Cut-and-paste transposition, which requires at least three phosphoryl transfer steps at each transposon end, therefore presents a mechanistic challenge. One solution to this challenge was revealed by the discovery of the DNA-hairpin cleavage-intermediate in V(D)J recombination and Tn10 transposition (Fig. ​(Fig.1)1) (34, 57). However, it is interesting to note that the existence of this intermediate was first suggested by Coen and colleagues on the basis of the genomic scars produced by excision of the hAT family transposon Tam3 in Antirrhinum majus (14).Open in a separate windowFIG. 1.Hairpin-processing reactions of opposite polarity. Most prokaryotic and eukaryotic members of the DDE family have hairpin intermediates of opposite polarity. In this paper, we refer to the two strands of DNA as “first strand” or “second strand” depending on the order of cleavage. The first strand therefore corresponds to the transferred and nontransferred strands of the prokaryotic and eukaryotic elements, respectively. Scissile phosphates are in red. The transposon end and RSS are shown as gray triangles. (Left panel) In Tn5 and Tn10, the first step of the reaction is a nick on the bottom (first) strand that exposes the 3′-OH at the end of the transposon. The second strand is cleaved by a direct transesterification reaction, which generates a “proximal-hairpin” intermediate on the transposon end (5, 34). Resolution by a nick at the tip of the hairpin yields a blunt transposon end. Distortion of the DNA helix can be detected by permanganate sensitivity of the T−1 and T+2 residues on the second strand. The insert shows the crystal structure of the Tn5 transposon end, highlighting the flipped base at position +2 (19). Two tryptophan residues are also shown. One acts as a “wedge” or “probe” residue inserted into the DNA helix, while the other provides stacking interactions that stabilize the flipped base. The W323 probe residue resides within the catalytic core close to the DDE residue E326, whereas the W298 stacking residue is in the inserted subdomain (see text for further details). Base flipping takes place after the first nick and is probably maintained for all subsequent steps, including integration (3, 7). (Right panel) In V(D)J recombination and the hAT family of transposons, the polarity of the reaction is reversed. The first nick is on the top strand providing a 3′-OH group on the flanking DNA (53, 71, 77). Transesterification yields a “distal hairpin” intermediate on the flanking DNA that is processed by the host. The positions of relevant thymidine residues in our substrates are indicated.All DDE family transposases, including RAG1, cut the DNA to expose the 3′-OH at the end of the element (or RSS). However, the fate of the opposite strand and the order of strand cleavage events vary within the group (reviewed in references13, 18, and 55). Some enzymes, such as the retroviral integrases and the bacteriophage Mu transposase, nick and integrate the 3′-OH directly without second-strand cleavage. The cut-and-paste transposons, which cleave both strands of DNA, can be divided into two groups. With some notable exceptions such as the piggyBac element, most prokaryotic family members cleave the bottom strand of the recombination site first, whereas most eukaryotic members cleave the top strand first (8, 10, 20, 41, 47, 48, 77). For those family members with a hairpin mechanism, the inverted polarity of the first step dictates the reversal of all subsequent steps (Fig. ​(Fig.1).1). In consequence, most eukaryotic members of the family can achieve transposition with one less phosphoryl transfer reaction than the prokaryotic members, which are obliged to resolve the hairpin intermediate. The eukaryotic members can simply release the hairpin ends or, as in the case of RAG, hand them on to host factors for further processing (40).Insight into the hairpin mechanism was provided by a crystal structure for the Tn5 transpososome, in which the penultimate base on the second, nontransferred, strand was flipped from the helix and stacked against a tryptophan side chain in the protein (Fig. ​(Fig.1)1) (19). The flipped base seemed to provide the steric freedom that is presumed to be required for making and resolving the hairpin intermediate. Two groups searched for a residue in RAG1 that performs a function equivalent to the stacking tryptophan in the Tn5 transposase (27, 45). This work identified several candidate residues on the basis of their respective mechanistic defects and their rescue by modified DNA substrates.Here we have further assessed the candidate stacking residues using biochemical techniques previously used to study the dynamics of base flipping in Tn5 and Tn10 transposition (6, 7). We have identified a distortion at position −1 of the V(D)J coding flank DNA. It is introduced after the first nick at the RSS and is therefore reminiscent of the flipped base at the end of Tn5. The distortion is perfectly correlated with the ability of wild-type and mutant RAG-RSS complexes to perform the hairpin step of the reaction. We conclude that this base is probably equivalent to the flipped base in Tn5. However, none of the candidate aromatic residues seems to fulfill the function of the putative stacking tryptophan residue. We therefore propose a model in which base flipping in RAG recombination is significantly different from that in Tn5 transposition.Canonical V(D)J recombination occurs within a 12/23 RSS paired complex (24, 36, 60, 72, 73). This restriction is known as the 12/23 rule. More recently a further restriction, the so-called “beyond 12/23” (B12/23) rule has been proposed to explain the exclusion of direct Vβ-to-Jβ joining in the TCR β region, despite the presence of appropriately oriented pairs of 12 and 23 RSSs (4, 21, 31, 32).Little is known of the mechanisms that enforce the 12/23 rule or coordinate cleavage on either side of the complex. However, during this work, we observed that the coding flank distortion was coupled on either side of a 12/23 RSS paired complex: the distortion of a nicked coding flank is suppressed by an unnicked partner. We present a model and discuss the biological significance of this conformational coupling and its relevance to the B12/23 rule.     

Environmental Factors Shape Sediment Anammox Bacterial Communities in Hypernutrified Jiaozhou Bay,China

Bacterial anaerobic ammonium oxidation (anammox) is an important process in the marine nitrogen cycle. Because ongoing eutrophication of coastal bays contributes significantly to the formation of low-oxygen zones, monitoring of the anammox bacterial community offers a unique opportunity for assessment of anthropogenic perturbations in these environments. The current study used targeting of 16S rRNA and hzo genes to characterize the composition and structure of the anammox bacterial community in the sediments of the eutrophic Jiaozhou Bay, thereby unraveling their diversity, abundance, and distribution. Abundance and distribution of hzo genes revealed a greater taxonomic diversity in Jiaozhou Bay, including several novel clades of anammox bacteria. In contrast, the targeting of 16S rRNA genes verified the presence of only “Candidatus Scalindua,” albeit with a high microdiversity. The genus “Ca. Scalindua” comprised the apparent majority of active sediment anammox bacteria. Multivariate statistical analyses indicated a heterogeneous distribution of the anammox bacterial assemblages in Jiaozhou Bay. Of all environmental parameters investigated, sediment organic C/organic N (OrgC/OrgN), nitrite concentration, and sediment median grain size were found to impact the composition, structure, and distribution of the sediment anammox bacterial community. Analysis of Pearson correlations between environmental factors and abundance of 16S rRNA and hzo genes as determined by fluorescent real-time PCR suggests that the local nitrite concentration is the key regulator of the abundance of anammox bacteria in Jiaozhou Bay sediments.Anaerobic ammonium oxidation (anammox, NH₄⁺ + NO₂⁻ → N₂ + 2H₂O) was proposed as a missing N transformation pathway decades ago. It was found 20 years later to be mediated by bacteria in artificial environments, such as anaerobic wastewater processing systems (see reference 32 and references therein). Anammox in natural environments was found even more recently, mainly in O₂-limited environments such as marine sediments (28, 51, 54, 67, 69) and hypoxic or anoxic waters (10, 25, 39-42). Because anammox may remove as much as 30 to 70% of fixed N from the oceans (3, 9, 64), this process is potentially as important as denitrification for N loss and bioremediation (41, 42, 73). These findings have significantly changed our understanding of the budget of the marine and global N cycles as well as involved pathways and their evolution (24, 32, 35, 72). Studies indicate variable anammox contributions to local or regional N loss (41, 42, 73), probably due to distinct environmental conditions that may influence the composition, abundance, and distribution of the anammox bacteria. However, the interactions of anammox bacteria with their environment are still poorly understood.The chemolithoautotrophic anammox bacteria (64, 66) comprise the new Brocadiaceae family in the Planctomycetales, for which five Candidatus genera have been described (see references 32 and 37 and references therein): “Candidatus Kuenenia,” “Candidatus Brocadia,” “Candidatus Scalindua,” “Candidatus Anammoxoglobus,” and “Candidatus Jettenia.” Due to the difficulty of cultivation and isolation, anammox bacteria are not yet in pure culture. Molecular detection by using DNA probes or PCR primers targeting the anammox bacterial 16S rRNA genes has thus been the main approach for the detection of anammox bacteria and community analyses (58). However, these studies revealed unexpected target sequence diversity and led to the realization that due to biased coverage and specificity of most of the PCR primers (2, 8), the in situ diversity of anammox bacteria was likely missed. Thus, the use of additional marker genes for phylogenetic analysis was suggested in hopes of better capturing the diversity of this environmentally important group of bacteria. By analogy to molecular ecological studies of aerobic ammonia oxidizers, most recent studies have attempted to include anammox bacterium-specific functional genes. All anammox bacteria employ hydrazine oxidoreductase (HZO) (= [Hzo]₃) to oxidize hydrazine to N₂ as the main source for a useable reductant, which enables them to generate proton-motive force for energy production (32, 36, 65). Phylogenetic analyses of Hzo protein sequences revealed three sequence clusters, of which the cladistic structure of cluster 1 is in agreement with the anammox bacterial 16S rRNA gene phylogeny (57). The hzo genes have emerged as an alternative phylogenetic and functional marker for characterization of anammox bacterial communities (43, 44, 57), allowing the 16S rRNA gene-based investigation methods to be corroborated and improved.The contribution of anammox to the removal of fixed N is highly variable in estuarine and coastal sediments (50). For instance, anammox may be an important pathway for the removal of excess N (23) or nearly negligible (48, 54, 67, 68). This difference may be attributable to a difference in the structure and composition of anammox bacterial communities, in particular how the abundance of individual cohorts depends on particular environmental conditions. Anthropogenic disturbance with variable source and intensity of eutrophication and pollution may further complicate the anammox bacterium-environment relationship.Jiaozhou Bay is a large semienclosed water body of the temperate Yellow Sea in China. Eutrophication has become its most serious environmental problem, along with red tides (harmful algal blooms), species loss, and contamination with toxic chemicals and harmful microbes (14, 15, 21, 61, 71). Due to different sources of pollution and various levels of eutrophication across Jiaozhou Bay (mariculture, municipal and industrial wastewater, crude oil shipyard, etc.), a wide spectrum of environmental conditions may contribute to a widely varying community structure of anammox bacteria. This study used both 16S rRNA and hzo genes as targets to measure their abundance, diversity, and spatial distribution and assess the response of the resident anammox bacterial community to different environmental conditions. Environmental factors with potential for regulating the sediment anammox microbiota are discussed.     

Evaluation of a Stochastic Inactivation Model for Heat-Activated Spores of Bacillus spp.

Heat activates the dormant spores of certain Bacillus spp., which is reflected in the “activation shoulder” in their survival curves. At the same time, heat also inactivates the already active and just activated spores, as well as those still dormant. A stochastic model based on progressively changing probabilities of activation and inactivation can describe this phenomenon. The model is presented in a fully probabilistic discrete form for individual and small groups of spores and as a semicontinuous deterministic model for large spore populations. The same underlying algorithm applies to both isothermal and dynamic heat treatments. Its construction does not require the assumption of the activation and inactivation kinetics or knowledge of their biophysical and biochemical mechanisms. A simplified version of the semicontinuous model was used to simulate survival curves with the activation shoulder that are reminiscent of experimental curves reported in the literature. The model is not intended to replace current models to predict dynamic inactivation but only to offer a conceptual alternative to their interpretation. Nevertheless, by linking the survival curve''s shape to probabilities of events at the individual spore level, the model explains, and can be used to simulate, the irregular activation and survival patterns of individual and small groups of spores, which might be involved in food poisoning and spoilage.Heat inactivation kinetics of bacterial spores is a well-researched field. Much of the work on its relation to foods has focused on the heat-resistant spores of Clostridia, particularly those of Clostridium botulinum, which to this date serves as the reference organism in sterility calculations of low-acid foods (8, 32). The thermal resistance of Bacilli spores, although also extensively studied, has received less attention in the literature on food preservation. This is primarily because they are unlikely to germinate and produce cells that will survive and divide under the anaerobic conditions in a sterilized food container. Yet the mere possibility of viable Bacillus spores being present in processed foods has become an issue of food safety and a security concern. For this reason, there is a renewed interest in these spores'' heat resistance (2, 3, 6, 7, 16, 30). One of the peculiarities of certain Bacillus spores, like those of Bacillus sporothermodurans or Bacillus stearothermophilus, is that many of them can remain dormant unless activated by heat. The result is a survival curve that exhibits an “activation shoulder,” as shown schematically in Fig. ​Fig.11 and with published data in Fig. ​Fig.2.2. Thus, modeling this survival pattern, where the number of spores initially grows rather than declines, must account for the heat''s dual role of being a lethal agent and activator at the same time.Open in a separate windowFIG. 1.A schematic view of a survival curve having an activation shoulder. S(t) is the ratio between the number N(t) of viable spores at time t and the initial number N₀. Notice the discrepancy between the two ways to estimate the number of dormant spores, represented by the dashed and dotted gray lines.Open in a separate windowFIG. 2.Demonstration of the fit of equation 1 (solid line) and equation 2 (dashed line) to survival curves of B. stearothermophilus spores at two temperatures. Notice the postpeak concavity of the curves. In such cases, the estimated number of dormant spores reached by the tangent method will depend on the experiment duration. The original experimental data are from Sapru et al. (25).Traditionally, the thermal inactivation of both Clostridia and Bacilli spores has been thought to follow first-order kinetics (9, 12, 31), an assumption that has been frequently challenged in recent years (18, 21, 33, 35). The most publicized model of the simultaneous heat activation and inactivation of Bacillus spores in food is that proposed by Sapru et al. (24, 25), which is an improved version of models proposed earlier by Shull et al. (29) and Rodriguez et al. (23). All of these authors and others (1, 17) assumed that the activation of dormant spores follows first-order kinetics and so does their inactivation before and after activation. The temperature dependence of the corresponding exponential rate constants was assumed to follow the Arrhenius equation.Peleg (18, 20) and van Boekel (33, 35) have shown that none of the above assumptions was necessary and that the same survival data on Bacillus stearothermophilus reported by Sapru et al. (25) and other investigators (5) can be described by different kinds of alternative four-parameter empirical models, which have a slightly better fit. This was evident not only visually (Fig. ​(Fig.2)2) but also as judged by statistical criteria (34). Fig. ​Fig.22 shows the fit of the “double Weibullian” model proposed by van Boekel (33). It has the following form: (1) where S(t) = N(t)/N₀ is the survival/activation ratio, N₀ and N(t) are the initial and momentary number of countable spores, respectively, and b₁, b₂, n₁, and n₂ are adjustable temperature-dependent constants. Figure 2 also shows the fit of an ad hoc empirical model, a hybrid between the double Weibullian model and one previously proposed (20) that can be written in the following form: (2) or (3) where a₁, b₁, t_c2, and m₂ are adjustable temperature-dependent parameters. According to this model, a₁ is the asymptote of the first term on the right, b₁ is a time characteristic of the activation, t_c2 is a characteristic time of the inactivation, and m₂ is a parameter that represents the curve''s postpeak concavity. The structure of equation 2 or 3 dictates that the number of dormant spores must be finite and cannot exceed N₀ × 10^a1, if the logarithm is base 10, or N₀ × exp(a₁), if it is base e. (A demonstration that generates realistic-looking activation/inactivation curves using equation 3 as a model is available from Wolfram Research [http://demonstrations.wolfram.com/SurvivalCurvesOfBacilliSporesWithAnActivationShoulder/].)Corradini and Peleg (5) proposed a way to estimate the initial number of dormant spores from survival curves having an activation shoulder using a similar model, which was originally described in Peleg (20). They suggested that the intersection of a tangent to the survival curve drawn at its postpeak region with the time axis (Fig. ​(Fig.1)1) is not a recommended method to estimate the number of dormant spores and that it can render unrealistically high values if used. Also, where there is no evidence that the survival curve in the postpeak region ever becomes a straight line; the same survival curve will yield different estimates of the dormant spores'' initial number depending on the experiment''s duration. Moreover, if in the postpeak region the survival ratio drop rate progressively increases, as it most probably does (Fig. ​(Fig.2)2) (20, 33), then the number of dormant spores estimated by the tangent extrapolation method will grow indefinitely, despite the fact that it must be finite (1). Also, since the exponential inactivation rate can be a function of time as well as of temperature, the applicability of the Arrhenius equation as a secondary model might come into question. The same can also be said about the log-linearity of the D value''s temperature dependence if used instead of the Arrhenius equation.The question that arises in light of all the above is whether one can construct a conceptual population dynamic model of the activation/inactivation of spores without assuming any fixed kinetic order. The biochemical and biophysical mechanisms that govern bacterial spore germination, activation, and inactivation have been thoroughly investigated (11, 13, 14, 15, 22, 26-28). Still, it is not clear how processes within an individual spore can be translated into activation and survival patterns at the population level and how their manifestation can be expressed in a mathematical model. Whenever a system has inherent variability and knowledge of its working is incomplete or merely insufficient to develop a model from basic principles, one can, and sometimes must, resort to a probabilistic modeling approach. The general objective of this work has been to explore the merits and limitations of this option by developing a stochastic model of Bacilli spores'' heat activation and inactivation and examining its properties. The goal has not been to develop a new method to predict the spores'' survival under dynamic conditions—rate versions of the existing empirical models such as equation 1, 2, or 3 seem to be quite suitable for that—but to offer an alternative interpretation of the patterns reported and discussed in the literature.     

Redesign,Reconstruction, and Directed Extension of the Brevibacterium linens C40 Carotenoid Pathway in Escherichia coli

In this study, the carotenoid biosynthetic pathways of Brevibacterium linens DSMZ 20426 were reconstructed, redesigned, and extended with additional carotenoid-modifying enzymes of other sources in a heterologous host Escherichia coli. The modular lycopene pathway synthesized an unexpected carotenoid structure, 3,4-didehydrolycopene, as well as lycopene. Extension of the novel 3,4-didehydrolycopene pathway with the mutant Pantoea lycopene cyclase CrtY₂ and the Rhodobacter spheroidene monooxygenase CrtA generated monocyclic torulene and acyclic oxocarotenoids, respectively. The reconstructed β-carotene pathway synthesized an unexpected 7,8-dihydro-β-carotene in addition to β-carotene. Extension of the β-carotene pathway with the B. linens β-ring desaturase CrtU and Pantoea β-carotene hydroxylase CrtZ generated asymmetric carotenoid agelaxanthin A, which had one aromatic ring at the one end of carotene backbone and one hydroxyl group at the other end, as well as aromatic carotenoid isorenieratene and dihydroxy carotenoid zeaxanthin. These results demonstrate that reconstruction of the biosynthetic pathways and extension with promiscuous enzymes in a heterologous host holds promise as a rational strategy for generating structurally diverse compounds that are hardly accessible in nature.Carotenoids, which are produced by many microorganisms and plants, belong to a class of pigment chemicals found in nature. These structurally diverse pigments have different biological functions such as coloration, photo protection, light-harvesting, and precursors for many hormones (3, 22). Carotenoids are commercially used as food colorants, animal feed supplements and, more recently, as nutraceuticals and as cosmetic and pharmaceutical compounds (19). Currently, only a few carotenoids can be produced commercially by chemical synthesis, fermentation, or isolation from a few abundant natural sources (13). The increasing industrial importance of carotenoids has led to renewed efforts to develop bioprocesses for large-scale production of a range of carotenoids, including lycopene, β-carotene, and more structurally diverse carotenoids (17, 21, 30, 31, 34). Interestingly, a recent study showed that carotenoids with more diverse structures tend to have higher biological activity than simple structures (1).Previously, in vitro evolution altered the catalytic functions of the carotenoid enzymes phytoene desaturase CrtI and lycopene cyclase CrtY (Fig. ​(Fig.1)1) and produced novel carotenoid structures of tetradehydrolycopene and torulene in Escherichia coli (27). Furthermore, these in vitro evolved pathways and redesigned C₃₀ carotenoid biosynthetic pathways were successfully extended with additional, wild-type carotenoid modifying enzymes and evolved enzymes (21), generating novel carotenoid structures (26).Open in a separate windowFIG. 1.Reconstructed and redesigned B. linens carotenoid biosynthetic pathway in the heterologous host E. coli. Carotenogenic enzymes of B. linens, P. ananatis, and R. capsulatus, which were used for the biosynthetic pathway reconstruction, are indicated by boldface letters. Idi (IPP isomerase), IspA (FPP synthase), CrtE (GGPP synthase), CrtB (phytoene synthase), CrtI (phytoene desaturase), CrtYcYd (lycopene cyclase), CrtU (β-carotene desaturase), CrtZ (β-carotene hydrolase), CrtY₂ (mutant lycopene cyclase), and CrtA (spheroidene monooxygenase). B. linens 3,3′-dihydroxyisorenieratene biosynthesis is indicated by dashed arrows.Beside in vitro evolution (23, 34), combinatorial biosynthesis with carotenoid-modifying enzymes in a heterologous host has often been used to generate structurally novel carotenoids (24, 32). This combinatorial biosynthetic approach basically relies on the functional coordination of pathway enzymes from different sources in a heterologous host (5, 19, 35). Carotenogenic enzymes tend to be promiscuous in their substrate specificity (33) and show unexpected/hidden activities (20) when expressed in heterologous host microorganisms. One example is the unusual activity of diapophytoene desaturase CrtN in E. coli, which resulted in structurally novel compounds (20). Therefore, utilizing the promiscuity of carotenogenic enzymes makes combinatorial biosynthesis one of the most powerful strategies to generate structurally novel carotenoids that cannot be accessed in nature.Yellow colored Brevibacterium linens is commonly used as a food colorant by the cheese industry (15). Interestingly, B. linens is known to synthesize aromatic ring-containing carotenoids, isorenieratene and its hydroxy derivatives (6, 7, 16). They are produced by seven carotenogenic enzymes expressed in B. linens: GGPP synthase CrtE, phytoene synthase CrtE, phytoene desaturase CrtI, lycopene cyclase CrtYcYd, β-carotene desaturase CrtU, and the cytochrome P450 (Fig. ​(Fig.1).1). Even though the carotenoid biosynthetic pathways of B. linens have been recently studied (6, 10), there have been no systematic functional study of downstream enzymes such as lycopene cyclase CrtYcYd in the biosynthetic pathway of B. linens in a heterologous environment.Therefore, in the present study, for the first time we reconstructed, redesigned, and rationally extended the B. linens carotenoids biosynthetic pathway in E. coli to investigate the flexibility of the pathway enzymes in a heterologous host. Using this approach, we obtained an unexpected structure 3,4-didehydrolycopene, 7,8-dihydro-β-carotene, torulene, and the asymmetric carotenoid, agelaxanthin A, from engineered B. linens carotenoid pathways in E. coli.     

Reengineering Escherichia coli for Succinate Production in Mineral Salts Medium

The fermentative metabolism of glucose was redirected to succinate as the primary product without mutating any genes encoding the native mixed-acid fermentation pathway or redox reactions. Two changes in peripheral pathways were together found to increase succinate yield fivefold: (i) increased expression of phosphoenolpyruvate carboxykinase and (ii) inactivation of the glucose phosphoenolpyruvate-dependent phosphotransferase system. These two changes increased net ATP production, increased the pool of phosphoenolpyruvate available for carboxylation, and increased succinate production. Modest further improvements in succinate yield were made by inactivating the pflB gene, encoding pyruvate formate lyase, resulting in an Escherichia coli pathway that is functionally similar to the native pathway in Actinobacillus succinogenes and other succinate-producing rumen bacteria.Succinic acid is used as a specialty chemical in the agricultural, food, and pharmaceutical industries (17, 32). It has also been identified by the U.S. Department of Energy as one of the top 12 building block chemicals (30), because it can be converted into a variety of products, including green solvents, pharmaceutical products, and biodegradable plastics (17, 32). Although succinic acid is currently produced from petroleum-derived maleic anhydride, considerable interest in the fermentative production of succinate from sugars has emerged during the past decade (9, 10, 17).Several natural succinate-producing rumen bacteria that have high rates of succinate production and high succinate yields, such as Anaerobiospirillum succiniciproducens (22), Actinobacillus succinogenes (13, 28), and “Mannheimia succiniciproducens” (15, 16), have been isolated. However, these strains require complex organic nutrients that increase the costs associated with production, purification, and waste disposal (15, 22, 28). Low levels of succinate are produced by native strains of Escherichia coli in complex and mineral salts media (1, 4). Most mutant strains of E. coli that have been described previously as succinate producers also require complex organic nutrients (18, 23-26, 29, 31). Many involve two-step aerobic and anaerobic processes (3, 23-25, 29) and the addition of foreign genes (5, 6, 23-26, 29, 31).Novel E. coli biocatalysts (KJ060, KJ071, and KJ073) for the anaerobic production of succinate in mineral salts medium have been developed recently without the use of foreign genes or resident plasmids (9, 10). These biocatalysts were developed by combining constructed mutations to eliminate alternative routes of NADH oxidation in the mixed-acid pathway with growth-based selection (metabolic evolution). In subsequent studies (33), these strains were found to have recruited the glucose-repressed (7), gluconeogenic pck gene (11, 12, 19, 21, 27), encoding phosphoenolpyruvate carboxykinase (PCK) (derepressed via a point mutation in the promoter region), to replace the native phosphoenolpyruvate carboxylase (ppc) and serve as the primary route for CO₂ fixation (Fig. ​(Fig.1).1). A second acquired mutation was also identified as a frameshift mutation in the carboxy terminus of ptsI, inactivating the phosphoenolpyruvate-dependent phosphotransferase system (33). Glucose uptake by the phosphotransferase system was functionally replaced by galactose permease (galP) and glucokinase (glk).Open in a separate windowFIG. 1.Anaerobic metabolism of E. coli using the mixed-acid fermentation pathway (data from reference 1). The native phosphotransferase system pathway for glucose uptake and the mixed-acid pathway for fermentation are shown with black arrows. Peripheral reactions for glucose uptake, carboxylation, and acetyl-CoA synthesis are shown as dotted green arrows and represent new metabolic functions that have been recruited for succinate production from glucose. Reactions that have been blocked by gene deletions or point mutations are marked with an X. pck* indicates a novel mutation that derepressed pck, allowing the enzyme to serve as the primary route for oxaloacetate production. Pyruvate (boxed) appears at two sites but is presumed to exist as a single intracellular pool.Based on these previous studies, we have now determined the core mutations needed to direct carbon flow from glucose to succinate in E. coli and have constructed new succinate-producing strains with a minimum of genetic change.     

The S Helix Mediates Signal Transmission as a HAMP Domain Coiled-Coil Extension in the NarX Nitrate Sensor from Escherichia coli K-12

In the nitrate-responsive, homodimeric NarX sensor, two cytoplasmic membrane α-helices delimit the periplasmic ligand-binding domain. The HAMP domain, a four-helix parallel coiled-coil built from two α-helices (HD1 and HD2), immediately follows the second transmembrane helix. Previous computational studies identified a likely coiled-coil-forming α-helix, the signaling helix (S helix), in a range of signaling proteins, including eucaryal receptor guanylyl cyclases, but its function remains obscure. In NarX, the HAMP HD2 and S-helix regions overlap and apparently form a continuous coiled-coil marked by a heptad repeat stutter discontinuity at the distal boundary of HD2. Similar composite HD2-S-helix elements are present in other sensors, such as Sln1p from Saccharomyces cerevisiae. We constructed deletions and missense substitutions in the NarX S helix. Most caused constitutive signaling phenotypes. However, strongly impaired induction phenotypes were conferred by heptad deletions within the S-helix conserved core and also by deletions that remove the heptad stutter. The latter observation illuminates a key element of the dynamic bundle hypothesis for signaling across the heptad stutter adjacent to the HAMP domain in methyl-accepting chemotaxis proteins (Q. Zhou, P. Ames, and J. S. Parkinson, Mol. Microbiol. 73:801-814, 2009). Sequence comparisons identified other examples of heptad stutters between a HAMP domain and a contiguous coiled-coil-like heptad repeat sequence in conventional sensors, such as CpxA, EnvZ, PhoQ, and QseC; other S-helix-containing sensors, such as BarA and TorS; and the Neurospora crassa Nik-1 (Os-1) sensor that contains a tandem array of alternating HAMP and HAMP-like elements. Therefore, stutter elements may be broadly important for HAMP function.Transmembrane signaling in homodimeric bacterial sensors initiates upon signal ligand binding to the extracytoplasmic domain. In methyl-accepting chemotaxis proteins (MCPs), the resulting conformational change causes a displacement of one transmembrane α-helix (TM α-helix) relative to the other. This motion is conducted by the HAMP domain to control output domain activity (reviewed in references 33 and 39).Certain sensors of two-component regulatory systems share topological organization with MCPs. For example, the paralogous nitrate sensors NarX and NarQ contain an amino-terminal transmembrane signaling module similar to those in MCPs, in which a pair of TM α-helices delimit the periplasmic ligand-binding domain (Fig. ​(Fig.1)1) (24) (reviewed in references 32 and 62). The second TM α-helix connects to the HAMP domain. Hybrid proteins in which the NarX transmembrane signaling module regulates the kinase control modules of the MCPs Tar, DifA, and FrzCD demonstrate that NarX and MCPs share a mechanism for transmembrane signaling (73, 74, 81, 82).Open in a separate windowFIG. 1.NarX modular structure. Linear representation of the NarX protein sequence, from the amino (N) to carboxyl (C) termini, drawn to scale. The four modules are indicated at the top of the figure and shown in bold typeface, whereas domains within each module are labeled with standard (lightface) typeface. The nomenclature for modules follows that devised by Swain and Falke (67) for MCPs. Overlap between the HAMP domain HD2 and S-helix elements is indicated in gray. The three conserved Cys residues within the central module (62) are indicated. TM1 and TM2 denote the two transmembrane helices. Helices H1 to H4 of the periplasmic domain (24), and the transmitter domain H, N, D, G (79), and X (41) boxes, are labeled. The HPK 7 family of transmitter sequences, including NarX, have no F box and an unconventional G box (79). The scale bar at the bottom of the figure shows the number of aminoacyl residues.The HAMP domain functions as a signal conversion module in a variety of homodimeric proteins, including histidine protein kinases, adenylyl cyclases, MCPs, and certain phosphatases (12, 20, 77). This roughly 50-residue domain consists of a pair of amphiphilic α-helices, termed HD1 and HD2 (formerly AS1 and AS2) (67), joined by a connector (Fig. ​(Fig.2A).2A). Results from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopy, Cys and disulfide scanning, and mutational analysis converge on a model in which the HD1 and HD2 α-helices form a four-helix parallel coiled-coil (7, 20, 30, 42, 67, 75, 84). The mechanisms through which HAMP domains mediate signal conduction remain to be established (30, 42, 67, 84) (for commentary, see references 43, 49, and 50).Open in a separate windowFIG. 2.HAMP domain extensions. (A) Sequences from representative MCPs (E. coli Tsr and Salmonella enterica serovar Typhimurium Tar) and S-helix-containing sensors (E. coli NarX, NarQ, and BarA, and S. cerevisiae Sln1p). The HAMP domain, S-helix element, and the initial sequence of the MCP adaptation region are indicated. Flanking numbers denote positions of the terminal residues within the overall sequence. Sequential heptad repeats are indicated in alternating bold and standard (lightface) typeface. Numbering for heptad repeats in the methylation region and S-helix sequences has been described previously (4, 8). Numbers within the HD1 and HD2 helices indicate interactions within the HAMP domain (42). Residues at heptad positions a and d are enclosed within boxes, residues at the stutter position a/d are enclosed within a thickly outlined box, and residues in the S-helix ERT signature are in bold typeface. (B) NarX mutational alterations. Deletions are depicted as boxes, and missense substitutions are shown above the sequence. Many of these deletions were reported previously (10) and are presented here for comparison. The phenotypes conferred by the alterations are indicated as follows: impaired induction, black box; constitutive and elevated basal, light gray box; reversed response, dark gray box; wild-type, white box; null, striped box.Coiled-coils result from packing of two or more α-helices (27). The primary sequence of coiled-coils exhibits a characteristic heptad repeat pattern, denoted as a-b-c-d-e-f-g (52, 61), in which positions a and d are usually occupied by nonpolar residues (reviewed in references 1, 47, and 80). For example, the coiled-coil nature of the HAMP domain can be seen in the heptad repeat patterns within the HD1 and HD2 sequences (Fig. ​(Fig.2A2A).Coiled-coil elements adjacent to the HAMP domain have been identified in several sensors, including Saccharomyces cerevisiae Sln1p (69) and Escherichia coli NarX (60). Recently, this element was defined as a specific type of dimeric parallel coiled-coil, termed the signaling helix (S helix), present in a wide range of signaling proteins (8). Sequence comparisons delimit a roughly 40-residue element with a conserved heptad repeat pattern (Fig. ​(Fig.2A).2A). Based on mutational analyses of Sln1p and other proteins, the S helix is suggested to function as a switch that prevents constitutive activation of adjacent output domains (8).The term “signaling helix” previously was used to define the α4-TM2 extended helix in MCPs (23, 33). Here, we use the term S helix to denote the element described by Anantharaman et al. (8).The NarX and NarQ sensors encompass four distinct modules (Fig. ​(Fig.1):1): the amino-terminal transmembrane signaling module, the signal conversion module (including the HAMP domain and S-helix element), the central module of unknown function, and the carboxyl-terminal transmitter module (62). The S-helix element presumably functions together with the HAMP domain in conducting ligand-responsive motions from the transmembrane signaling module to the central module, ultimately regulating transmitter module activity.Regulatory output by two-component sensors reflects opposing transmitter activities (reviewed in reference 55). Positive function results from transmitter autokinase activity; the resulting phosphosensor serves as a substrate for response regulator autophosphorylation. Negative function results from transmitter phosphatase activity, which accelerates phosphoresponse regulator autodephosphorylation (reviewed in references 64 and 65). We envision a homogeneous two-state model for NarX (17), in which the equilibrium between these mutually exclusive conformations is modulated by ligand-responsive signaling.Previous work from our laboratory concerned the NarX and other HAMP domains (9, 10, 26, 77) and separately identified a conserved sequence in NarX and NarQ sensors, the Y box, that roughly corresponds to the S helix (62). Therefore, we were interested to explore the NarX S helix and to test some of the predictions made for its function. Results show that the S helix is critical for signal conduction and suggest that it functions as an extension of the HAMP HD2 α-helix in a subset of sensors exemplified by Sln1p and NarX. Moreover, a stutter discontinuity in the heptad repeat pattern was found to be essential for the NarX response to signal and to be conserved in several distinct classes of HAMP-containing sensors.     

Metabolic Engineering of the Tricarboxylic Acid Cycle for Improved Lysine Production by Corynebacterium glutamicum

In the present work, lysine production by Corynebacterium glutamicum was improved by metabolic engineering of the tricarboxylic acid (TCA) cycle. The 70% decreased activity of isocitrate dehydrogenase, achieved by start codon exchange, resulted in a >40% improved lysine production. By flux analysis, this could be correlated to a flux shift from the TCA cycle toward anaplerotic carboxylation.With an annual market volume of more than 1,000,000 tons, lysine is one of the dominating products in biotechnology. In recent years, rational metabolic engineering has emerged as a powerful tool for lysine production (16, 18, 22). Hereby, different target enzymes and pathways in the central metabolism could be identified and successfully modified to create superior production strains (1, 2, 5, 8, 10, 17-20). The tricarboxylic acid (TCA) cycle has not been rationally engineered so far, despite its major role in Corynebacterium glutamicum (6). From metabolic flux studies, however, it seems that the TCA cycle might offer a great potential for optimization (Fig. ​(Fig.1),1), which is also predicted from in silico pathway analysis (13, 22). Experimental evidence comes from studies with Brevibacterium flavum exhibiting increased lysine production due to an induced bottleneck toward the TCA cycle (21). In the present work, we performed TCA cycle engineering by downregulation of isocitrate dehydrogenase (ICD). ICD is the highest expressed TCA cycle enzyme in C. glutamicum (7). Downregulation was achieved by start codon exchange, controlling ICD expression on the level of translation.Open in a separate windowFIG. 1.Stoichiometric correlation of lysine yield (%), biomass yield (g/mol) and TCA cycle flux (%; entry flux through citrate synthase) determined by ¹³C metabolic flux analysis achieved by paraboloid fitting of the data set (parameters were determined with Y0 = 105.1, a = −1.27, b = 0.35, c = −9.35 × 10⁻³, d = −11.16 × 10⁻³). The data displayed represent values from 18 independent experiments with different C. glutamicum strains taken from previous studies (1-3, 11, 12, 15, 23).