Global Histone H4 acetylation R788 was not affected by HDAC8 knockdown or by selective inhibitor treatment [34]. In contrast, HDAC8 knockdown in some cell lines and treatment with c5 or c6 resulted in a strong increase of acetylated α-tubulin. The latter finding is in accord with previous ABT-888 molecular weight findings in HeLa and HEK293 cells [45]. The cytoplasmic protein α-tubulin is especially a substrate of HDAC6 which is predominantly localized in the cytoplasm [23]. HDAC6 influences the cytoskeleton and cell motility via deacetylation

of α-tubulin and other cytoskeleton proteins [46]. In vitro, c5 and c6 do not inhibit HDAC6 efficiently. Thus, the best explanation for these observations is that in vivo HDAC8 directly or indirectly influences α-tubulin acetylation. Similar discrepancies between in vitro and in vivo activity of an isoenzyme-selective HDAC inhibitor on tubulin AR-13324 acetylation have been observed by others for valproic acid [47]. These effects on α-tubulin acetylation may relate to the inhibition of cell migration by c5 and c6 we observed in UC cell lines. However, inhibition of HDAC6 as such does not inhibit migration of UCC as efficiently as the HDAC8 inhibitors c5 and c6 [48]. The effects of siRNA mediated knockdown of HDAC8 on cell cycle and apoptosis were limited and few significant effects were seen, such as a decreased S-phase fraction in VM-CUB1 and small

changes in thymidylate synthase and p21 expression. In the neuroblastoma cell line BE (2)-C, a G0/G1 arrest has been detected after siRNA-mediated knockdown of HDAC8. This G0/G1 arrest induced by HDAC8 knockdown was associated with p21 mRNA upregulation [34]. In contrast, no effect on the cell cycle was observed in the hepatocellular carcinoma cell Cell press lines BEL-7402 and Hep-G2 [36]. This observation fits with our own marginal effects after siRNA-mediated

HDAC8 knockdown. The level of apoptosis induction in BEL-7402 and Hep-G2 cells after siRNA-mediated targeting of HDAC8 were comparable to the increase of the subG1-fraction in individual urothelial carcinoma cell lines after targeting of HDAC8 [36]. Concerning the use of inhibitors, effects of pharmacological inhibition on cell cycle distribution by c2 were, as expected, only minor. In contrast, pharmacological inhibition by c5 or c6 resulted in a significant albeit low increase of the sub-G1 fraction in two out of five cell lines and in an apparent G2/M-arrest in four out of five cell lines. Consequently, p21 increased in two cell lines and thymidylate synthase decreased in all but one. Conclusions HDAC8 is deregulated in UCCs resulting in variable mRNA and protein expression levels. Suppression and pharmacological inhibition of HDAC8 had significant, but overall minor impacts on cell proliferation, clonogenic growth and migration. These effects were comparable to findings in other cancer entities. Furthermore, pharmacological inhibition of HDAC8 induced a G2/M-arrest.

caliginosus DNA; therefore the LAU1F-CB2 primer pair was used for species identification. The latter amplified all Macrolophus-DNA, although the LAU1-primer was designed

to specifically amplify M. caliginosus-DNA [35]. Results are summarized in Table 1. 16S rRNA gene sequencing A PCR assay was carried out on a pool of adult M. pygmaeus males and females of the laboratory strain using general primers targeting the bacterial 16S rRNA gene. A total of 23 clones were sequenced, VE-822 mouse varying in length depending on the use of primer pair 27F-806R or 27F-1525R (Table 2). These sequences were compared with the non-redundant (nr) nucleotide database at the National Center for Biotechnology (NCBI) using BLASTN. Three of the cloned bacteria can be considered as endosymbionts, namely Wolbachia and two Rickettsia species (Table 3). The two Rickettsia species were BMN 673 cost identified using the primer pair 27F-806R. In order to obtain approximately 1500 base pairs of their

16S rRNA gene, a PCR using a forward SN-38 supplier primer based on the partially known sequences of the two Rickettsia species was designed and combined with the general bacterial 1492R primer (Rick1F-1492R, Table 2). One of these Rickettsia species exhibited a 99% similarity to Rickettsia limoniae and the Rickettsia endosymbiont of the water beetle Deronectes platynotus. The second one was 99% similar to Rickettsia bellii and the Rickettsia endosymbiont of the pea aphid Acyrthosiphon pisum. Other cloned bacteria are not regarded as endosymbiotic bacteria, but rather as environmental or gut bacteria

(Table 3). Table 3 Partial 16S rDNA sequences isolated in this study by cloning and PCR-DGGE. The accession number of the closest relative is indicated between brackets. Closest known relative Phylogenetically related class Sequenced length (bp) Identity (%) Accession no. 16S rRNA PCR cloning of M. pygmaeus         Rickettsia limoniae strain Brugge (AF322443) Alpha-proteobacteria 1422 99 HE583202 Rickettsia GPX6 bellii (L36103) Alpha-proteobacteria 1422 99 HE583203 Wolbachia endosymbiont of Culex quinquefasciatus (AM999887) Alpha-proteobacteria 1461 98 HE583204 Uncultured bacterium (GQ360069) Gamma-proteobacteria 1496 99 HE583205 Uncultured bacterium (HM812162) Firmicutes 767 100 HE583206 Uncultured bacterium (FJ512272) Firmicutes 764 99 HE583207 Uncultured bacterium (GU118480) Beta-proteobacteria 743 99 HE583208 PCR-DGGE*         1) Wolbachia endosymbiont of Polydrusus pilifer (JF304463) Alpha-proteobacteria 135 100 HE583209 2) Rickettsia bellii (L36103) Alpha-proteobacteria 135 99 HE583210 3) Uncultured bacterium (JF011887) Gamma-proteobacteria 160 100 HE583211 4) Uncultured bacterium (JF011887) Gamma-proteobacteria 160 99 HE583212 5) Rickettsia limoniae strain Brugge (AF322443) Alpha-proteobacteria 137 100 HE583213 6) Uncultured Streptococcus sp.

CrossRef 75. Suzuki K, Matusubara H: Recent advances in p53 research and cancer treatment. J Biomed Biotech 2011, 2011:978312. 76. John Nemunaitis, PI3K Inhibitor Library Ian Ganly, Fadlo Khuri, James Arseneau, Joseph Kuhn, Todd McCarty, Stephen Landers, Phillip Maples, Larry Rome, Britta Randlev, Tony Reid, Sam Kaye, David Kirn: Selective replication and oncolysis in p53 mutant tumors with ONYX-015, an E1B-55kD gene-deleted adenovirus, in patients with advanced head and neck cancer: A phase II trial. Cancer Res 2000, 60:6359. 77. Boeckler FM,

Joerger AC, Jaggi G, Rutherford TJ, Veprintsev DB, Fersht AR: Targeted rescue of a destabilised mutant of p53 by an in silico screened drug. Proc Natl Acad Sci USA 2008,105(30):10360–10365.PubMedCrossRef 78. Rippin TM, Bykov VJ, Freund SM, Selivanova G, Wiman KG, Fersht A: Characterisation of the p53-rescue drug CP-31398 in vitro and in living cells. Oncogene 2002,21(14):2119–2129.PubMedCrossRef 79. Shangary S, Wang S: Mocetinostat cell line Small-molecule inhibitors

of the MDM2-p53 protein-protein interaction to reactivate p53 function: a novel approach for cancer therapy. Annu Rev Pharmacol Toxicol 2008, 49:223–241.CrossRef 80. Shangary S, Qin D, McEachern D, Liu M, Miller RS, Qiu S, Nikolovska-Coleska Z, Ding K, Wang G, Chen J, Bernard D, Zhang J, Lu Y, Gu Q, Shah RB, Pienta KJ, Ling X, Kang S, Guo M, Sun Y, Yang D, Wang : Temporal activation of p53 by a specific MDM2 inhibitor is selectively toxic to tumours and leads to complete tumor growth inhibition. Proc Natl Acad Sci USA 2008,105(10):3933–3938.PubMedCrossRef 81. Lain

S, PXD101 manufacturer Hollick JJ, Campbell J, Staples OD, Higgins M, Aoubala M, McCarthy A, Appleyard V, Murray KE, Baker L, Thompson A, Mathers J, Holland SJ, Stark MJ, Pass G, Woods J, Lane DP, Westwood NJ: Discovery, in vivo activity, and mechanism of action of a small-molecule p53 activator. Cancer Cell 2008,13(5):454–463.PubMedCrossRef 82. Kuball J, Schuler M, Antunes Ferreira E, Herr W, Neumann M, Obenauer-Kutner L, Westreich L, Huber C, Wölfel T, Theobald M: Generating p53-specific cytotoxic T lymphocytes by recombinant adenoviral vector-based vaccination in mice, but not man. Gene Ther 2002,9(13):833–843.PubMedCrossRef 83. Svane IM, Pedersen AE, Johnsen HE, Nielsen D, Kamby C, Gaarsdal E, Nikolajsen K, Buus S, Claesson MH: Vildagliptin Vaccination with p53-peptide-pulsed dendritic cells, of patients with advanced breast cancer: report from a phase I study. Cancer Immunol Immunother 2004,53(7):633–641.PubMedCrossRef 84. Vermeij R, Leffers N, van der Burg SH, Melief CJ, Daemen T, Nijman HW: Immunological and clinical effects of vaccines targeting p53-overexpressing malignancies. J Biomed Biotechnol 2011, 2011:702146.PubMedCrossRef 85. Dai Y, Lawrence TS, Xu L: Overcoming cancer therapy resistance by targeting inhibitors of apoptosis proteins and nuclear factor-kappa B. Am J Tranl Res 2009,1(1):1–15. 86.

Although many efforts and applications have been

achieved for these novel carbon films, it is still a great challenge to develop a novel method to prepare the films at a large scale. Herein, we report a new method to prepare graphene-Ag composite films with excellent and improved properties, which are fabricated by the large-scale assembly of graphene oxide PF-02341066 chemical structure films, followed by in situ reduction of graphene oxide films together with Ag+ by ascorbic acid. The mechanical and electrical properties of the obtained graphene-Ag composite films are also BAY 73-4506 nmr investigated. Methods Materials The natural graphite powder (carbon content 99.999%) in the experiment was purchased from Qingdao Tianyuan Carbon Co. Ltd, Qingdao, China. Other solvents Epigenetic Reader Domain inhibitor and reagents were of analytical reagent grade and used as received. Preparation of graphene-Ag composite films Graphene oxide was synthesized through the modified Hummers method [37] as stated in our previous reports [2, 18, 38]. Prior to reduction, the synthesized graphene oxide (0.15 g) was dispersed in 50 mL of deionized water by ultrasonic treatment (1,000 W, 40 kHz) for 2 h, and then, the yellow-brown dispersion was poured into a polytetrafluoroethylene (PTFE) plate with a diameter of 11.5 cm and heated at 80°C for 24 h. Finally, the brown-black films with a diameter

of 10 to 11 cm and thickness of 10 μm could be obtained as shown in Figure 1a. In order to reduce the graphene oxide films, ascorbic acid was used as a reducing agent

[38, 39]. To obtain graphene films, 150 mg ascorbic acid was dissolved in water, followed by soaking the graphene oxide films into the solution for a certain time in order to determine an optimized period. In addition, to obtain graphene-Ag composite films, 150 mg ascorbic acid was dissolved into the AgNO3 aqueous solution (100 mL, 2 to 300 mg), and the graphene oxide films were soaked in the mixed solution for 5 h. The schematic illustration of two chemical synthesis routes is described in Figure 2. After washing with deionized water, the final black paper-like graphene films and graphene-Ag composite films (Figure 1b) were obtained after heated at 80°C for 2 h, respectively. Figure 1 Photographs of samples. (a) Epothilone B (EPO906, Patupilone) Graphene oxide films and (b) graphene-Ag composite films with the amount of 10 mg AgNO3. Figure 2 Schematic illustration of the chemical route for the synthesis of graphene-Ag composite films. Characterizations Atomic force microscope (AFM) image was taken with the Multimode Nanoscope V scanning probe microscopy system (Veeco Instruments Inc., Plainview, NY, USA) using tapping mode with Picoscan v5.3.3 software. The morphology of the films were observed using a scanning electron microscope (SEM) using a Carl Zeiss ULTRA 55 (Carl Zeiss, Oberkochen, Germany) with energy dispersive X-ray (EDX) spectrometry mode. The crystal structures of the films were examined by X-ray diffraction (XRD; D/MAX-2200, Rigaku, Tokyo, Japan) with Cu Kα (λ = 1.

This is accomplished by redistributing the MK-8776 percentage of total ELS points in each option category based upon their pHQ scores (i.e. the most beneficial option will account for the greatest number of points within the category and so on). The number of units of each option is then the total points divided by the options ELS points value. Again, expenditure on categories is maintained to better reflect current enrolment and preferences. This allows the absolute area covered by ELS options to vary, however the total area enrolled in ELS, and the subsequent taxpayer payments,

will remain the same. $$P_ic = \mathop \sum \nolimits P_c \times pHQ_ic$$where P ic is the total ELS points accounted by option i in category c, P c is the total ELS points produced by options in category c. Model C also maintains current ELS budget, however, under this model the ELS points of all options are pooled regardless of their category and the redistribution is based upon the habitat quality benefits of S3I-201 price each option in relation to all other options, regardless of their category. As such the most beneficial of all available options will represent the greatest percentage of total redistributed ELS points and so

on. As with model B, this allows the number of units of each option to change, although now there is a degree of substitution between option categories and which may affect their prevalence in the overall ELS. To prevent the outputs of this model from being dominated by arable and grassland options, many of

which are worth several hundred ELS points, the ELS points for hedge/ditch and plot/tree based options were multiplied by 1,000 (assuming 1 m2/unit of hedge/ditch options) Bay 11-7085 and 10 (assuming 100 m2/unit of plot options) respectively to scale points of these options relative to 1 ha. $$T_i = \mathop \sum \nolimits T \times tHQ_i$$ T i represents the ELS points accounted by option i, T is the summed points value of all ELS options concerned and tHQ i is the percentage of total HQ of all options represented by each option. For each model the total ELS points and number of units for each option were recalculated to compare with the baseline. Once the ELS composition of each model was calculated the total number of units for each option in each model and the baseline were then multiplied by the average per annum costs per unit (See Table 7 in Appendix) using the costs from the SAFFIE (2007) and Nix (2010), following the establishment and management MG-132 chemical structure guidelines laid out in each option (Natural England 2010). Many options had low or no cost.

In one of the strains (BS64), it was associated with better autoaggregation and greater surface hydrophobicity. This strain has been selleck chemical reported to be an inducer of T-helper 2 cytokines; in contrast, NCC2705 had the lowest surface hydrophobicity of the four strains and has been reported to induce T-helper 1 cytokines [28]. This study showed that proteomic approach may help researchers understand the differential effects of bifidobacteria

and be useful for identifying bifidobacteria with probiotic potential. Methods Strains, media and growth conditions B. longum NCC2705 was kindly provided by the Nestlé Research Center (Lausanne, Switzerland). B. longum CUETM 89-215 (BS89), BS49 and BS64 were isolated from the dominant fecal flora of healthy infants [28]. Strains were cultured on Wilkins-Chalgren anaerobe agar (Oxoid) supplemented with 1% (w/v) D-glucose, 0.05% (w/v) L-cysteine, 0.5% (v/v) Tween 80 (WCB) and incubated for 48 https://www.selleckchem.com/products/ABT-263.html hrs at 37°C in a chamber under anaerobic conditions (CO2:H2:N2, 10:10:80). After genomic DNA extraction, Bifidobacterium strains were identified by multiplex PCR and amplification and sequencing of the 16S rRNA, as previously described [37]. TGYH broth

(tryptone peptone, 30 g l-1; glucose, 5 g l-1; yeast extract, 20 g l-1; haemin, 5 g l-1) was used for cell growth prior to protein extraction. Three independent growth experiments were performed for each strain to extract cytosolic proteins. β-galactosidase activity was visualized on Luria-Bertani (LB) (Oxoid) agar plates supplemented with X-gal (40 mg l-1). Genotyping using PFGE PFGE was performed as previously described using Quisqualic acid the XbaI restriction enzyme [29]. Gels were run using a clamped homogeneous electric-field apparatus (CHEF-DRIII, Bio-Rad), and Staphylococcus aureus NCTC 8325 DNA was used as a reference. GelCompar Defactinib software (Bio-Rad) was used for cluster analysis (Applied Maths) with

the Dice correlation coefficient, and a dendrogram was produced with the unweighted pair-group method using the arithmetic averages clustering algorithm. Cytosolic protein extraction and 2D-electrophoresis Cytosolic cell extracts were obtained from 300 ml of culture in TGYH medium that was collected at the mid-log exponential growth phase (OD600 of 0.8-0.9). Cytosolic protein extraction and 2D-electrophoresis were performed as previously described [21]. The protein concentration of each bacterial extract was measured using the Coomassie Protein Assay Reagent kit (Pierce Biotechnology) according to the manufacturer’s instructions. For electrophoresis, proteins from bifidobacterial extracts (350 μg) were loaded onto strips (17 cm) with a pH range of 4 to 7 (Bio-Rad), focused for 60,000 V·h, and the second dimension was carried out using a 12.5% SDS-polyacrylamide gel.

When cultured in TSB as free-living cells, wild type and all mutant strains showed the similar growth rates, as reported in previous buy MEK162 study [20]. In contrast, when incubated in PBS for 24 h, wild type and mutants lacking long and/or short fimbriae formed distinct biofilms (Figure

1 and Table 1). Wild type strain 33277 formed biofilms with a dense basal monolayer and dispersed microcolonies. Compared with the wild type, the long fimbria mutant KDP150 formed patchy and sparser biofilms with a significantly buy GF120918 greater distance between fewer peaks, although mean peak height was almost the same as that of the wild type strain. In contrast, the short fimbria mutant MPG67 developed cluster and channel-like Selleckchem Tariquidar biofilms consisting of significantly taller microcolonies compared to the wild type. Similar to MPG67, the mutant (MPG4167) lacking both types of fimbriae also formed thick biofilms with significantly taller microcolonies than the wild type. Viability of the cells in biofilms of each strain was tested by colony count and confirmed at 24 h (data not shown). These results suggest that the long fimbriae are involved in initial attachment and organization of biofilms by P. gingivalis, whereas the short fimbriae have a suppressive regulatory role for these steps. Figure

1 Homotypic biofilm formation by P. gingivalis wild-type strain and mutants in PBS. P. gingivalis strains were stained with CFSE (green) and incubated in PBS for 24 hours. After washing, the biofilms that developed on the coverglass Arachidonate 15-lipoxygenase were observed with a CLSM equipped with a 40× objective. Optical sections were obtained along the z axis at 0.7-μm intervals, and images of the x-y and x-z planes were reconstructed

with an imaging software as described in the text. Upper panels indicate z stacks of the x-y sections. Lower panels are x-z sections. P. gingivalis strains used in this assay are listed in Table 4. The experiment was repeated independently three times with each strain in triplicate. Representative images are shown. Table 1 Features of biofilms formed by P. gingivalis wild-type strain and mutants in PBS   Peak parametersa) Strain Number of peaks Mean distance between peaks (μm) Mean peak height (μm) ATCC33277 (wild type) 28.5 ± 3.3 3.0 ± 0.2 2.8 ± 0.4 KDP150 (ΔfimA) 14.7 ± 2.4** 5.4 ± 1.0** 2.7 ± 0.8 MPG67 (Δmfa1) 29.3 ± 2.0 3.6 ± 0.2 16.6 ± 0.8** MPG4167 (ΔfimAΔmfa1) 30.5 ± 1.9 3.1 ± 0.2 12.7 ± 0.5** KDP129 (Δkgp) 25.5 ± 2.1 3.6 ± 0.3 12.7 ± 1.3** KDP133 (ΔrgpAΔrgpB) 13.0 ± 2.6** 8.4 ± 1.3** 23.2 ± 2.8** KDP136 (ΔrgpAΔrgpBΔkgp) 30.5 ± 2.4 3.2 ± 0.2 12.7 ± 0.7** a) Number of peaks was evaluated in an area sized 90 (x axis) × 2 (y axis) μm. The mean ± SE of 10 areas was shown. **p < 0.

O157 cell pellet and lysate fractions from Experiment I (LB, dRF, fRF) were concentrated using spin filters (MW cutoff 5000 Daltons), and digested with trypsin prior to tandem mass spectrometry (MS/MS) as described previously [17]. The enzymatically-digested samples were injected onto a capillary trap (LC Packings PepMap) and desalted for 5 min with a flow rate of 3 μl/min of 0.1% v/v acetic acid. The samples were loaded onto an LC Packing® C18 Pep Map nanoflow HPLC column. The elution gradient of the HPLC column started at 3% solvent B, 97% solvent A and finished at 60% solvent B, 40% solvent

A for 95 min RG-7388 for protein identification. Solvent A consisted of 0.1% v/v acetic acid, 3% v/v acetonitrile (ACN), and 96.9% v/v H2O. Solvent B consisted of 0.1% v/v acetic acid, 96.9% v/v ACN, and 3% v/v H2O. LC-MS/MS analysis was carried out on a hybrid quadrupole-TOF mass spectrometer (QSTAR

elite, see more Applied Biosystems, Framingham, MA). The focusing potential and ion spray voltage was set to 225 V and 2400 V, respectively. The information-dependent acquisition (IDA) mode of operation was employed GDC-0068 purchase in which a survey scan from m/z 400–1800 was acquired followed by collision-induced dissociation (CID) of the four most intense ions. Survey and MS/MS spectra for each IDA cycle were accumulated for 1 and 3 s, respectively. Tandem mass spectra were extracted by ABI Analyst version 2.0. All MS/MS samples were analyzed using Mascot (Matrix Science, London, UK; version 2.2.2). Mascot was set up to search NCBI with taxonomy Bacteria database assuming the digestion enzyme trypsin. Mascot was searched with a fragment ion mass tolerance of 0.50 Da and a parent ion tolerance of 0.50 Da. Iodoacetamide derivative of Cys, deamidation of Asn and Gln, oxidation of Met, were specified in Mascot as variable modifications. Scaffold (version Scaffold-03-3-2, Proteome

Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 95.0% probability as specified by the Peptide ID-8 Prophet algorithm [22]. Protein identifications were accepted if they could be established at greater than 99.0% probability and contained at least 2 identified unique peptides. Proteins with single peptide hits were included if they exhibited high confidence based on low false discovery rates [23]. Relative protein abundance was estimated using the normailized total spectral counts [24]. Protein probabilities were assigned using the Protein Prophet algorithm [25]. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony.

2D). In cluster D the dctA gene coding for the DctA dicarboxylate import system was found. The DctA dicarboxylate import system [37] is well characterised and a broad substrate range has been identified [38]. This dicarboxylate import system is known to be essential for symbiosis since it is supposed to click here provide the cells in the bacteroid state with tricarbonic acid (TCA) cycle intermediates from the host plant, e.g. succinate, malate, and

fumarate. A group of genes in this cluster points to an induced fatty acid degradation. The gene smc00976 is coding for a putative enoyl CoA hydratase and smc00977 and smc02229 are coding for putative acyl CoA dehydrogenase proteins. With glpD, a gene coding for a glycerol-3-phosphate dehydrogenase find more involved in the glycerol degradation could also be found in cluster D. The transient induction of genes involved in fatty acid degradation might be related to a lack of energy or the modification of the membrane lipid composition. Cluster E contains genes involved in nitrogen metabolism, ion transport and BIBF 1120 manufacturer methionine metabolism Cluster E consists of 22 genes whose expression was lowered in response to the pH shift. The expression was lowered up to 10 minutes after pH shift and then stayed constant until the end of the time course experiment (Fig. 2E). Cluster E contains genes involved in nitrogen metabolism.

The gene glnK codes for a PII acetylcholine nitrogen regulatory protein activated under nitrogen limiting conditions and forms together with amtB, which encodes a high affinity ammonium transport system, an operon. The GlnK protein could also be identified as lower expressed after a short exposure of S. medicae cells to low pH [27].

It was argued by Reeve et al. that this observation might be related to some crosstalk between nitrogen and pH sensing systems during the early pH adaptation [27]. With metF, metK, bmt, and ahcY four genes involved in the methionine metabolism were also grouped in this cluster, while two other met genes were grouped into cluster F (metA) and cluster G (metH), respectively. The distribution of these genes to two other clusters of down-regulated genes might be due to the fact the met genes are not organised in an operon, but dispersed over the chromosome. S-adenosylmethionine is formed from methionine by MetK and is the major methylation compound of the cell that is needed e.g. for polyamine- or phosphatidylcholine biosynthesis. The connection between the down-regulation of the methionine metabolism and the pH response is not clear. It was shown that various abiotic stresses result in a rapid change of cellular polyamine levels [39–41]. Several genes belonging to ion uptake systems were located in cluster E, like the complete sitABCD operon and phoC and phoD of the phoCDET operon. The sitABCD operon codes for a manganese/iron transport system [42, 43].

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