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E. coli has two oxygen sensors: FNR (fumarate-nitrate reductase) and ArcBA (Anoxic Redox Control, two component control systems). FNR directly senses the oxygen, while the interaction of ArcB with oxygen is indirect one via quinone pool. Out of theree quionones in E. coli, which one (oxidized and reduced forms of all three types) play roles to what extent in what direction (inhibiting/activating) is much debatable. I would like to see some intuitive level arguments for why a cell, even in principle, need to have two sensors for oxygen?
It is not uncommon for cells to have parallel pathways for same outcome. This ensures foolproof response and makes the system robust. E.coli also has another sensor for aerotaxis (Aer and Tsr proteins). See my answer on your previous post and the linked paper.
Also look for coherent feed forward network motifs.
Oxygen and redox sensing by two-component systems that regulate behavioral responses: behavioral assays and structural studies of aer using in vivo disulfide cross-linking
A remarkable increase in the number of annotated aerotaxis (oxygen-seeking) and redox taxis sensors can be attributed to recent advances in bacterial genomics. However, in silico predictions should be supported by behavioral assays and genetic analyses that confirm an aerotaxis or redox taxis function. This chapter presents a collection of procedures that have been highly successful in characterizing aerotaxis and redox taxis in Escherichia coli. The methods are described in enough detail to enable investigators of other species to adapt the procedures for their use. A gas flow cell is used to quantitate the temporal responses of bacteria to a step increase or decrease in oxygen partial pressure or redox potential. Bacterial behavior in spatial gradients is analyzed using optically flat capillaries and soft agar plates (succinate agar or tryptone agar). We describe two approaches to estimate the preferred partial pressure of oxygen that attracts a bacterial species this concentration is important for understanding microbial ecology. At the molecular level, we describe procedures used to determine the structure and topology of Aer, a membrane receptor for aerotaxis. Cysteine-scanning mutagenesis and in vivo disulfide cross-linking procedures utilize the oxidant Cu(II)-(1,10-phenanthroline)(3) and bifunctional sulfhydryl-reactive probes. Finally, we describe methods used to determine the boundaries of transmembrane segments of receptors such as Aer. These include 5-iodoacetamidofluorescein, 4-acetamido-4-disulfonic acid, disodium salt (AMS), and methoxy polyethylene glycol maleimide, a 5-kDa molecular mass probe that alters the mobility of Aer on SDS-PAGE.
Non-invasive detection of intracellular O2 is of particular importance since it is one of the key metabolites of obligate and facultative aerobic organisms. Cellular O2 is a prominent indicator for oxygen-dependent metabolic activities, such as aerobic respiration or oxygen dependent synthesis and degradation of cellular components [1, 2]. In addition, various biological, pathological and biotechnological processes are controlled by O2 limitation, including biofilm formation and host-pathogen interactions [3–7], hypoxia induced inflammatory processes , tumor pathophysiology [9–12] as well as microbial fermentation processes used for bioremediation and the production of food, feed and biofuels [13–16].
To date, different minimally invasive fluorescence and phosphorescence based O2-sensitive probes have been developed for imaging molecular oxygen in cells and tissues. Among them, platinum(II)-porphyrin dyes are widely used for analyzing hypoxia-induced responses of mammalian cells [17–19]. Alternatively, the green fluorescent protein (GFP) and its variants can be applied as genetically encoded intracellular probes that are specifically expressed and can be selectively targeted within defined cells and tissues. In this context, at least two 'passive' GFP-based oxygen sensors have been developed for estimating intracellular oxygen levels in E. coli. Here, GFP was applied as a reporter protein expressed under control of oxygen-responsive E. coli promoters [20, 21]. Additionally, oxygen sensitive photoactivation of GFP-mediated red fluorescence was applied for in vivo imaging of oxygen in mammalian cells and organs [22–24].
Remarkably, molecular oxygen can currently not be analyzed in vivo by genetically encoded FRET-based biosensors, although these biosensors constitute one of the most widespread classes of fluorescent molecular probes used for the non-invasive quantitative analysis of intracellular compounds including Ca 2+ , Zn 2+ , Cl - , pH, H2O2, ATP, maltose, sucrose, ribose and glucose [25–27]. With respect to oxygen sensing, however, GFP-like proteins, which are commonly used as donor and acceptor domains of FRET biosensors, exhibit a major drawback: Their autocatalytic chromophore synthesis strictly depends on the presence of molecular oxygen [28, 29] and thus the fluorescence signal intensity basically does not reflect the amount of synthesized reporter protein . Therefore, GFP and its color variants can not solely be used as fluorescent biosensor domains for accurate O2 determination.
Recently, we developed a novel class of fluorescent proteins which carry flavin mononucleotide (FMN) as chromophore . In contrast to GFP-like FPs, the fluorescence signal of these FMN-based fluorescent proteins (FbFP) is independent of cellular oxygen and thus FbFP can be used as quantitative in vivo real-time reporter protein under aerobic as well as anaerobic conditions [30, 31]. Here, we report the construction and application of the first genetically encoded FRET-based biosensor for oxygen named FluBO which consists of the oxygen-insensitive FbFP donor domain and the hypoxia-sensitive enhanced yellow fluorescent protein (YFP) acceptor domain. We further show that its FRET efficiency dynamically responds to changing O2 values in living bacterial cells.
Rhizobia are alpha-proteobacteria that engage in symbiosis with legume plants . The bacteria convert inert atmospheric N2 into biologically accessible ammonia and provide it to their plant host in a process called nitrogen fixation [2,3]. All biological fixation is catalysed by the nitrogenase enzyme complex that evolved before the Great Oxygenation Event and requires near-anoxic conditions to function [4–6]. However, rhizobia are obligate aerobes and must respire to meet the high energy demands of nitrogen fixation [7,8]. These competing requirements create an ‘oxygen paradox’ in symbiotic nitrogen fixation [9,10]. To overcome this paradox, intricate cooperation between rhizobia and their plant partners has evolved (reviewed in [11,12]). Legume plants host rhizobia in dedicated root nodules which form where bacteria have entered the plant root, usually via infection threads (reviewed in [13,14]). Nodules create a near-anoxic internal environment suitable for nitrogenase activity [15–17]. To produce this environment, oxygen (O2) is captured and shuttled to bacteroids by plant leghaemoglobins [18–21]. The concentration of remaining free O2 in the core nitrogen fixation zone of nodules is as low as 20–50 nM [22,23]. Rhizobia undergo a radical lifestyle change after nodule entry to survive and fix nitrogen in these conditions (reviewed in [24,25]). In indeterminate nodules, such as those produced by Pisum sativum (pea), rhizobia are initially free-living upon entry [26,27]. They then undergo irreversible lifestyle changes as they move from the nodule tip to its core [28,29]. Beginning in zone II and accelerating in the II-III interzone, rhizobia terminally differentiate into quasi-organelle bacteroids specialized for nitrogen fixation [30,31]. Zone III of indeterminate nodules contains differentiated bacteroids which are actively fixing nitrogen . Rhizobial regulatory mechanisms sensitive to O2 tension are essential for successful differentiation into bacteroids and the establishment of a productive symbiosis [33–35].
Multiple O2 sensors have evolved in rhizobia, three of which are widespread and often co-exist within the same organism [11,36]. The first is the membrane-bound FixL protein, which forms a two-component system (TCS) with the FixJ receiver protein (reviewed in [37,38]). Under microaerobic conditions, FixL phosphorylates FixJ, which in turn induces expression of the fixK transcription factor [39–41]. FixK induces expression of downstream genes by binding as a dimer to an ‘anaerobox’ motif (TTGAT-N4-ATCAA) upstream of their promoters [42,43].
The second common O2 sensor is a variant of FixL called hybrid FixL (hFixL) [44,45]. This forms an alternative TCS with FxkR acting as the receiver protein. FxkR is not a FixJ homolog but similarly induces expression of fixK, by binding to an upstream ‘K-box’ motif (GTTACA-N4-GTTACA) . The third O2 sensor is the FnrN transcription factor. Like FixK, FnrN binds the anaerobox motif as a dimer and both are close homologs of the E. coli anaerobiosis regulator FNR [47–49]. Unlike FixK but like FNR, FnrN contains an N-terminal cysteine-rich cluster that makes the protein a direct sensor of O2 [50–53]. The FixL and hFixL sensors are known to become active at relatively mildly microaerobic conditions, including in free-living rhizobia [54–56]. FnrN is likely to be far less O2 tolerant. The O2 sensitivity of FnrN has not been determined, but the E. coli FNR homolog is active only under anaerobic conditions [57–59]. All symbiotic rhizobia studied to date employ at least one of these three sensors . It is common for these sensors to coexist, notably in Rhizobium leguminosarum biovar viciae VF39, multiple strains of Ensifer meliloti (previously Sinorhizobium meliloti) and Rhizobium etli CFN42 [44,45,60–62].
Further emphasizing the importance of O2 regulation in symbiotic nitrogen fixation, rhizobia also employ the O2 sensing NifA transcription factor to regulate their final differentiation into nitrogen fixing bacteroids (for reviews see [38,63]). NifA oxygen sensitivity is thought to derive from a metal-binding cysteine-rich motif in an inter-domain linker of the protein [64–66]. The protein has a large regulon, notably including nitrogenase components such as nifH [67–70]. Expression of nifA is typically auto-regulated in rhizobia, often via read-through from an upstream gene or operon that is NifA regulated, in many cases fixABCX [69,71–73]. In Rlv3841, a fixABCX operon is found directly upstream of nifA, suggesting such a read-through NifA auto-activation mechanism. Usually, neither expression of nifA nor the activity of the protein is directly regulated by the three O2 sensors described above . One notable exception is E. meliloti, where nifA is regulated by the FixLJ system [74–76]. There is no evidence that FixK or FnrN directly regulates nifA expression in Rlv3841.
There appears to be a spectrum among rhizobia, with some species segregating oxygen sensors into separate pathways, whilst in other species these sensors have partially or completely merged into a combined hierarchical pathway [77,78]. Where oxygen sensors are in separated pathways, redundancy often exists. In these situations the loss of one oxygen sensor does not abolish nitrogen fixation activity [79,80]. By contrast, where sensors have been merged into a single regulatory pathway, some components are individually essential . Thus, loss of one oxygen sensor can severely impair nitrogen fixation even if other sensors remain.
In R. leguminosarum bv. VF39, knocking out FnrN or hFixL reduced nitrogen fixation to 30% or 50% of WT respectively, suggesting a non-hierarchical, redundant arrangement . The hFixL-FxkR-FixK pathway of R. etli CFN42 is dispensable as a double fixK mutant had no effect on nitrogen fixation, whilst a double fnrN mutant reduced fixation to 20% of WT levels. By contrast, R. etli CFN42 appears to employ a complex hierarchical pathway, with multiple homologs of FixK and FnrN regulating each other’s expression [61,62]. Species encoding homologs of only hFixL or FnrN have also been found. Rhizobium leguminosarum biovar viciae UPM791 contains two FnrN homologs but neither FixL nor hFixL . It is unknown whether the two FnrN proteins respond to different O2 concentrations or act in a redundant fashion. E. meliloti 1021 contains no FnrN homolog but a well-studied FixLJ system and appears to have homologs of hFixL and FxkR [82–84].
To examine the relationship between hFixL and FnrN, we studied the model organism Rhizobium leguminosarum biovar viciae 3841 (Rlv3841) which employs both sensors (Fig 1) [85,86]. Rlv3841 has a single chromosome whose gene names start with RL, and six megaplasmids pRL7-12 whose gene names start with e.g. pRL9. The main symbiotic plasmid is pRL10, but many symbiotic genes are also found on pRL9 including a copy of the fixNOQP and fixGHIS operon. Rlv3841 encodes two copies of hfixL, which we named hfixL9 (pRL90020 on pRL9) and hfixLc (RL1879 on the chromosome), with 54.9% identity at the protein level. The strain also contains two homologs (58% identity) of fxkR, fxkR9 (pRL90026) and fxkRc (RL1881). It has three putative fixK genes, which we designated fixK9a (pRL90019), fixK9b (pRL90025) and fixKc (RL1880). The fixK9a and fixK9b sequences have 53% amino acid identity, whilst fixKc shares 38% and 47% identity with these proteins, respectively. Both fixK9a-hfixL9 and fixKc-hfixLc appear to form operons (Fig 1B and 1D). Rlv3841 has one copy of fnrN (RL2818), regulated by two anaeroboxes. A similar dual-anaerobox arrangement exists in Rlv UPM791, where FnrN positively and negatively auto-regulates its own expression . Binding of FnrN to the distal anaerobox induces fnrN transcription and binding to the proximal anaerobox represses it. Auto-activation of FnrN has also been reported in Rhizobium etli CNPAF512 . FixK regulation of fnrN expression is likely as it also binds anaeroboxes, but this had not been investigated.
Oxygen is shown in red diamonds. Proteins are shown as ovals, operator sites as squares and genes as pointed rectangles. Transcription start sites are shown as right-angled arrows. Line endings indicate activation (arrows), inhibition (blunt end) and translation (circle). (A) The single pathway formed by the two sensors acts in two stages. Stage I starts under microaerobic conditions and can function outside the nodule. In this stage, hFixL is active but FnrN is not. hFixL activates FxkR, which binds to the K-box operator (orange “K” squares) to induce expression of fixK. FixK binds to anaerobox operators (blue “A” squares) to induce expression, including upstream of fixNOQP (dashed line) and fnrN. Once oxygen in the bacteria reaches near-anaerobic levels, FnrN becomes active and stage II begins. Like FixK, FnrN binds anaeroboxes. It auto-regulates fnrN both positively and negatively and induces fixNOQP expression. (B) Rlv3841 has multiple copies of several oxygen regulation genes and many are arranged in clusters. On megaplasmid pRL9, fixK9a forms an operon with hfixL9, regulated by a K-box. This operon is adjacent to fixNOQP9, regulated by an anaerobox. (C) fixK9b and fxkR9 are adjacent, with an anaerobox and a K-box in their intergenic region. (D) The Rlv3841 chromosome also has a cluster, containing fxkRc, fixKc and hfixLc. Unlike the similar clusters on pRL9, the intergenic region of this cluster contains no anaerobox or K-box operators. (E) The fnrN gene is not part of a cluster and is positively and negatively regulated by a distal and proximal anaerobox, respectively. Details of transcription start site, anaerobox and K-box locations can be found in Table 1.
A study in R. leguminosarum VF39 found that microaerobic expression of fnrN also requires RpoN . This finding has not been replicated elsewhere, and its significance remains unclear. Work in R. etli CNPAF512 showed that fnrN is not controlled by RpoN in that organism . Rlv3841 encodes one putative rpoN gene (RL0422), but we found no RpoN binding sites upstream of the Rlv3841 fnrN transcription start site. RpoN therefore does not appear to be required for fnrN expression in Rlv3841.
A parallel arrangement of hFixL-FxkR-FixK and FnrN in Rlv3841 would produce redundancy, whereas an arrangement in series would create hierarchy between the two regulators. Our goal is therefore to understand how the two sensors interact in Rlv3841 and to provide insight into why they coexist.
Microbial spoilage and foodborne diseases cause significant economic and productivity losses. There is a need for novel approaches and antimicrobial treatments to extend shelf life of products, improve quality and microbial safety, and reduce spoilage and waste, and new assessment methods. Traditional assays for testing the toxicity of antimicrobials are time consuming, labour intensive, give crude estimations of toxicity, and cannot analyse complex samples such as crude food homogenates. Using a model antimicrobial compound Lauroyl Arginate Ethyl Ester (LAE), we describe a new analytical methodology based on optical oxygen sensing and respirometry to investigate the effects of various antimicrobial treatments on pure bacterial cultures, meat microbiota and packaged meat samples. By measuring and analysing the time profiles of O2 probe signal (phosphorescence lifetime) in incubating test samples, we were able to visualise the toxic effects of LAE on the different bacterial specie, generate time and dose response curves, calculate EC50 and generation times of test organisms. The new multi-parametric toxicity testing platform allows for rapid, automated and parallel analysis of multiple samples under a range of antimicrobial concentrations and conditions.
Design and engineering of E. coli metabolic sensor strains with a wide sensitivity range for glycerate
Microbial biosensors are used to detect the presence of compounds provided externally or produced internally. The latter case is commonly constrained by the need to screen a large library of enzyme or pathway variants to identify those that can efficiently generate the desired compound. To address this limitation, we suggest the use of metabolic sensor strains which can grow only if the relevant compound is present and thus replace screening with direct selection. We used a computational platform to design metabolic sensor strains with varying dependencies on a specific compound. Our method systematically explores combinations of gene deletions and identifies how the growth requirement for a compound changes with the media composition. We demonstrate this approach by constructing a set of E. coli glycerate sensor strains. In each of these strains a different set of enzymes is disrupted such that central metabolism is effectively dissected into multiple segments, each requiring a dedicated carbon source. We find an almost perfect match between the predicted and experimental dependence on glycerate and show that the strains can be used to accurately detect glycerate concentrations across two orders of magnitude. Apart from demonstrating the potential application of metabolic sensor strains, our work reveals key phenomena in central metabolism, including spontaneous degradation of central metabolites and the importance of metabolic sinks for balancing small metabolic networks.
Keywords: Auxotrophy Constraint-based metabolic model Growth selection Synthetic biology.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.
13.4.8 Programmed Control
Because of the inherent time-varying character of batch and fed-batch fermentations, maintaining a constant environment or constant values of metabolic variables is not always the optimal control strategy. Depending on the process, changes in variables such as pH and temperature at critical times can improve production rate and yield. Varying the rate of the feed is important in fed-batch bakers’ yeast fermentations to minimise the Crabtree effect and maximise biomass production. Feed rate is also manipulated in E. coli fermentations to reduce by-product synthesis. In secondary-metabolite fermentations, specific growth rate should be high at the start of the culture but, at high cell densities, different conditions are required to slow growth and stimulate product formation. Similar strategies are needed to optimise protein synthesis from recombinant organisms. Expression of recombinant product is usually avoided at the start of the culture because cell growth is adversely affected however, later in the batch an inducer is added to switch on protein synthesis.
For many bioprocesses, a particular time sequence of pH, temperature, dissolved-oxygen tension, feed rate and other variables is required to develop the culture in such a way that productivity is maximised. A control strategy that can accommodate wide-ranging changes in fermentation variables is programmed control, also known as batch fermenter scheduling. In programmed control, the control policy consists of a schedule of control functions to be implemented at various times during the process. This type of control requires a detailed understanding of the requirements of the process at various stages and a reasonably complete and accurate mathematical model of the system.
MATERIALS AND METHODS
Mycobacterium tuberculosis H37Rv genomic DNA was obtained from Dr. Jeffery Cox of the University of California, San Francisco. Ampicillin was purchased from Fisher Biotech while chloramphenicol was obtained from Roche, hemin from Fluka Biochemica, dithionite from JT Baker, and IPTG from Promega. Lysozyme and phenylmethylsulfonyl fluoride were from Sigma. Protease inhibitors (antipain, leupeptin and pepstatin), chloramphenicol, Fast Start High Fidelity PCR system, and Amplitaq polymerase were obtained from Roche. A 1 kbplus DNA ladder was purchased from Life technologies. Argon and CO were from Matheson Tri-Gas.
Simply Blue Safe Stain, In Vision Histag In-Gel Stain, See Blue Plus 2 protein markers, S.O.C. medium, along with the gel apparatus (Novex MiniCell), NuPage 12% Bis-Tris gels and NuPage MOPS SDS running buffer were purchased from Invitrogen. The E. coli XL-10 gold, BL21DE3, and XL-1 Blue cells were from Stratagene.
The TOPO TA cloning kit was obtained from Invitrogen and the QuikChange Mutagenesis kit from Stratagene. DNA purification was carried out using QIAgen kits. The restriction enzymes, T4 DNA ligase, and alkaline phosphatase were from New England Biolabs. HisTrap TM HP columns were obtained from GE Healthcare, while dialysis tubing was purchased from Spectrum laboratories, Inc.
The pET23a+ plasmid was purchased from Novagen. The pTGroE plasmid was kindly provided by Dr. Shunsuke Ishii from the Laboratory of Molecular Genetics, Riken Tsukuba Life Science Center, Japan.
The primers were designed using GCG software package version 10.3 for UNIX from the University of Wisconsin. Custom primers were synthesized by Invitrogen. Amino acid analyses were performed at the University of California, Davis. DNA samples were sequenced at the University of California, Berkeley.
Cloning the Full-length DevS Gene
The DevS gene was amplified from Mycobacterium tuberculosis H37Rv genomic DNA using a PCR PTC-200 Peltier Thermal Cycler from MJ Research and the Fast Start High Fidelity PCR system from Roche. A 10 min. initial denaturation at 94 ଌ was followed by 35 cycles: 94 ଌ 1 min., 45 ଌ 1.5 min, 72 ଌ 3 min and a 10 min final extension at 72 ଌ. The forward primer (GGATAGGGCATATGACAACAGGGGGCCTC) included an NdeI cleavage site while the reverse primer (CCAAACGGGGATCCGAAGAGCTACTGCGACAAC) contained a BamH1 site. The reaction mixture contained 4% DMSO. The product obtained in this reaction was reamplified using the same conditions in order to obtain sufficient amounts of PCR product.
TOPO TA Cloning
3’ Poly-adenine overhangs were added to the purified PCR product using Amplitaq DNA polymerase. The TOPO TA cloning reaction was performed for 30 min at room temperature, according to the manufacturer’s instructions using the pCR2.1-TOPO vector. Plasmid DNA was purified from several colonies of TOP10 cells transformed with the TOPO TA cloning reaction product. Insertion of the DevS gene was verified using restriction digests (either NcoI or NotI) and the correct sequence of the DevS gene was confirmed by DNA sequencing.
Subcloning of DevS642
The first 642 bp which code for the N-terminal GAF domain were amplified using the same PCR conditions and the following primers: CCGCCGCCATATGCATCATCATCATCATCACGAGAACTTATATTTTCAAGGAATGACAACAGGGGGCCTCGTCGAC (forward primer containing a 6-His tag and an NdeI cleavage site) and CGGACAAGCTTCTATTACGACTGACGCGCCTTAGCCTGCTG (the reverse primer that includes a HindIII site). The purified PCR product was digested with NdeI and HindIII and ligated into pET23a+ cleaved with the same restriction enzymes as well as with alkaline phosphatase. XL-10 gold ultracompetent cells were transformed with the ligation product. After restriction analysis, the plasmid DNA was also submitted for sequencing in order to confirm the correct sequence.
Mutagenesis of His149 of DevS642
The QuikChange Mutagenesis kit from Stratagene was used to mutate His149 to an alanine according to the manufacturer’s instructions. The mutagenic primers used were: CGATTGGTTTTCCGCCGTATGCCCCGCCGATGCGTACCTTCCT (forward primer) AGGAAGGTACGCATCGGCGGGGCATACGGCGGAAAACCAATCG (reverse primer). The constructs were submitted for DNA sequencing in order to confirm the correct sequence.
Expression of DevS642 and Full-length DevS
BL21gold DE3 cells were co-transformed with pET23a+DevS642 and pT-GroE. The cells were grown on LB plates containing both ampicillin (50 μg/mL) and chloramphenicol (34 μg/mL). Five starter cultures were then inoculated with one colony each. The five cultures were then pooled and used to inoculate flasks containing 1.5 L LB medium as well as the antibiotics ampicillin (100 μg/mL) and chloramphenicol (34 μg/mL). The cells were grown to an optical density of OD600 0.8 at 37 ଌ and 230 rpm. Hemin was added before induction (45 mg/4.5 mL NaOH 0.1 N for each 1.5 L culture). Protein expression was induced with IPTG at a final concentration of 1 mM and the flasks were kept at 18 ଌ for 20 h. The cells were harvested by centrifugation at 5000 rpm for 25 min. Besides E. coli BL21DE3, two other cell lines were tested: Rosetta 2 and DH5α. DH5α cells did not express the desired protein either when they were transformed only with the plasmid coding for DevS642 or when they were co-transformed in order to provide the GroEL/ES complex as well. Rosetta 2 cells were also tested, because several codons of lower usage in E. coli were identified inside the gene. It was found, however, that the expression level was not significantly enhanced. The full-length DevS was cloned into pET23a+ using the same strategy as in the case of the wt DevS642 protein. The full-length DevS was co-expressed with the GroEL/ES complex and then purified using the same conditions.
Expression of ApoDevS642
The same procedure was followed as for the heme bound protein except i) no hemin was added, and ii) extra steps were taken to remove iron and cobalt from the culture medium. A published procedure was used and modified to exclude cobalt salts from the mineral mix (23).
Expression of the H149A Mutant of DevS642
The mutant could be expressed both as the heme bound protein and as the apoprotein following the method employed in the case of wt DevS642. In order to obtain the apoprotein, the lack of hemin addition was sufficient and no further steps were required in order to decrease contamination with the heme bound recombinant protein. The apoprotein of the H149A mutant was obtained using LB medium.
The cells were lysed in phosphate buffer pH 7.6 (50 mM NaH2PO4, 10% glycerol, 200 mM NaCl, 1% Triton X-100, 0.5 mg/mL lysozyme, protease inhibitors: antipain 1 μg/mL, leupeptin 1 μM, pepstatin 1 μM, PMSF 0.1 mM). Then the mixture was incubated with shaking at 37 ଌ for 10 min. The cell membranes were disrupted by repeated sonication cycles at 50% using a Branson sonifier 450 from VWR Scientific, while cooling on ice. The insoluble fraction was isolated by centrifugation at 35000 rpm for 1 h at 4 ଌ. The cell lysate was applied to a 5 mL His trap column at a rate of 1 mL/min. The column was then washed with 20 and 50 mM imidazole in phosphate buffer (50 mM NaH2PO4, 10% glycerol, 500 mM NaCl, 50 mL at a rate of 2 mL/min). The recombinant protein eluted with 200 mM imidazole in phosphate buffer (50 mL, 1 mL/min). The sample was then dialyzed and the fractions that were not pure were repurified on a His trap column to provide the pure protein. This procedure was successful for the heme containing wt DevS642 and H149A, and also for the apoprotein of the H149A mutant. The buffer was replaced with 20 mM Hepes buffer (150 mM NaCl pH 8) for the isolation of apoDevS642.
The protein content for the wt DevS642 was determined by amino acid analysis at the University of California, Davis. The yield of soluble protein was 16 mg/L culture in the case of co-expression with the heat shock proteins GroEL/ES. The yield of soluble protein when it was expressed without chaperones was 2.3 mg/L culture.
Heme Content Determination of Wt DevS642
Sodium hydroxide 5 N (5 μL) and pyridine (18 μL) were added to the protein sample (80 μL of the ferric complex). The oxidized spectrum was recorded and then sodium dithionite (a few crystals) was added to obtain the reduced spectrum. The absorbance at 539 and 556 nm was used to determine the heme content according to the published protocol (24). The heme content was determined to be 97%.
Size Exclusion Chromatography of Wt DevS642
The oligomeric state of the recombinant protein DevS642 was established using a Superdex 75 (FPLC) column in a phosphate buffer system (50 mM phosphate, 200 mM NaCl pH 7.6). The absorbance of the eluate was monitored at two wavelengths, 280 and 406 nm. Dextran (1 mg/ml) was used to determine the void volume. The calibration curve was obtained with the following protein standards: albumin (MW 66000, 10 mg/mL), alcohol dehydrogenase (MW 150000, 5 mg/mL), carbonic anhydrase (MW 29000, 3 mg/mL), cytochrome c (MW 12400, 2 mg/mL). DevS642 is 96% monomeric (MW 30269 as estimated from the gel filtration assay) and 4% dimeric (MW 61518).
Hemin Titrations of Wt ApoDevS642
A 500 μL protein sample (typically 5 μM concentration in Hepes 20 mM, NaCl 150 mM, 10% glycerol buffer) was titrated with a hemin solution. Aliquots of 0.5 μL of a 0.106 mg/mL hemin solution were added and the difference spectrum was recorded 10 min after each addition (the reference cuvette contained buffer and the same amounts of hemin.) To obtain the dissociation constant, sorbance 407-350 nm was plotted as a function of hemin concentration and the data points in the titration were fit to the following equation: sorbance = Amax/1 + KD/[hemin] (25).
Cyanide and Azide Titrations of Wt DevS642
The concentration of DevS642 was determined based on the intensity of the Soret peak at 407 nm. A 500 μL sample (usual concentration 5 μM) was used in these assays. The initial spectrum of the protein in phosphate buffer (50 mM phosphate and 200 mM sodium chloride) was recorded and then difference spectra were acquired 5 min. after each addition (typically 0.5 μL) of the ligand to both the reference cuvette and the cuvette containing the protein solution. Sodium azide and potassium cyanide were prepared as aqueous solutions in the same buffer. The increase in absorbance at 424 nm (cyanide) or 422 (azide) was plotted as a function of ligand concentration and the data were fit to a rectangular hyperbola (the azide titration) or the quadratic tight binding equation in the case of cyanide (26).
Electronic Absorption and Resonance Raman Spectroscopy
Typical enzyme concentrations used were
100 μM. Biomax-10 ultrafiltration devices (Millipore) were used for buffer exchange and for concentrating the protein. Reduction to the ferrous state was achieved by adding microliter aliquots of 25 mM sodium dithionite solution to an argon-purged sample in the Raman capillary cell and was monitored by UV-visible spectroscopy directly in the capillary using a Cary 50 spectrometer. 12 CO (Airgas) and 13 CO (99% 13 C, ICON Stable Isotopes) adducts were obtained by injecting CO through a septum-sealed capillary containing argon-purged, reduced protein (
20 μL). O2 (Airgas), 18 O2 (99% 18 O, ICON Stable Isotopes), NO (Aldrich), and 15 N 18 O (98% 15 N and 95% 18 O, Aldrich) adducts were generated using the same procedure after excess dithionite was removed from the reduced sample with desalting spin columns (Zebra ™ 0.5 mL, Pierce). These procedures were performed in a glovebox with a controlled atmosphere of less than 1-ppm of O2 (Omni-Lab System, Vacuum Atmospheres Company). RR spectra were obtained using a custom McPherson 2061/207 spectrograph (0.67 m with variable gratings) equipped with a Princeton Instruments liquid N2-cooled CCD detector (LN-1100PB). Kaiser Optical supernotch filters were used to attenuate Raleigh scattering. A Krypton laser (Innova 302, Coherent) and a He/Cd laser (Liconix 4240NB) were used for the 413- and 442-nm excitations, respectively. Spectra were collected in a 90° scattering geometry on samples at room temperature. Frequencies were calibrated relative to indene and CCl4 and are accurate at cm 𢄡 . CCl4 was also used to check the polarization conditions. The integrity of the RR samples, before and after laser illumination, was confirmed by direct monitoring of their UV-visible spectra in the Raman capillaries.
Complications in E. coli-related infection have been mainly attributed to biofilm formation. Biofilm is considerably recalcitrant to antibiotics as compared to its planktonic culture. Escherichia coli biofilm formation is an intricate process which involves a number of steps such as initial adhesion, early development, maturation and dispersion. These steps are governed by a number of genes that serve specific functions in the formation of the biofilm. Type I fimbriae of E. coli plays a crucial role in its attachment to the surface and maturation is further facilitated by autotransporters and EPS. Recent discoveries have also identified stress resistance genes in the biofilm-formation process that help the biofilm to survive in hostile environments. The rpoS gene is majorly responsible for regulating genes and structural proteins involved in the synthesis and degradation of biofilm, under stress conditions.
Escherichia coli biofilm has been found to be resistant to a number of antibiotics, mostly accredited to putative multidrug resistance pump. The development of the extracellular matrix and the observed increased resistance to common antibiotics create a challenge to control the infections caused by E. coli biofilms. Recently there have been advances in exploring and developing new approaches and therapeutic methods to cure E. coli biofilm-related infections.
Molecular and structural understanding of E. coli biofilm has led to the advances in targeting specific agents to curtail infections. Type I pili of E. coli are crucial for the adhesion and initiation of E. coli biofilm formation. The curlicides and pilicides have been designed against curli subunit protein CsgA and type I pili, respectively, and have been shown to inihibit bacterial biofilm. The combination of phages have shown to complement lysis of bacteria through different mechanism of action and yielded promising results. Bacterial biofilm has been notorious in mounting resistance and phytochemicals and AMPs are able to address this issue through their diverse mechanism to target organisms.
One of the major problems faced by these remedial agents is stability and low bioavailability. Natural compound efficacy can be improved by incorporating them in nanoparticles or coating on a particular surface. Silver nanoparticles have shown great promise especially in coating the medical devices and wound dressings and were found to be effective against E. coli biofilm both in vitro and in vivo mouse model. An antimicrobial nanospray JUC, which was sprayed on a catheter was found to be efficacious in restricting E. coli biofilm formation. These new methods hold a great promise but the issues concerning in vivo efficacy, toxicity and large-scale production need to be addressed before these potential therapeuticals can reach the clinical stage.
We acknowledge funding by the Bundesministerium für Wirtschaft und Technologie within the framework of Zentrales Innovationsprogramm Mittelstand (ZIM). We also wish to thank Steffen Wagner and Stefan Ortleb for excellent technical assistance.
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Fig. S1 The influence of PFD immersion on the photosynthetic output of a sycamore leaf.
Fig. S2 The effect of the photosynthesis inhibitor DCMU on light-dependent oxygen production in the sycamore leaf.
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