extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Engineering

text:
Monounsaturated Fatty Acids Are Substrates for Aldehyde Generation in Tellurite-Exposed Escherichia coli

Reactive oxygen species (ROS) damage macromolecules and cellular components in nearly all kinds of cells and often generate toxic intracellular byproducts. In this work, aldehyde generation derived from the Escherichia coli membrane oxidation as well as membrane fatty acid profiles, protein oxidation, and bacterial resistance to oxidative stress elicitors was evaluated. Studies included wild-type cells as well as cells exhibiting a modulated monounsaturated fatty acid (MUFA) ratio. The hydroxyaldehyde 4-hydroxy 2-nonenal was found to be most likely produced by E. coli, whose levels are dependent upon exposure to oxidative stress elicitors. Aldehyde amounts and markers of oxidative damage decreased upon exposure to E. coli containing low MUFA ratios, which was paralleled by a concomitant increase in resistance to ROS-generating compounds. MUFAs ratio, lipid peroxidation, and aldehyde generation were found to be directly related; that is, the lower the MUFAs ratio, the lower the peroxide and aldehyde generation levels. These results provide additional evidence about MUFAs being targets for membrane lipid oxidation and their relevance in aldehyde generation.

Introduction
Oxidative damage is a widespread phenomenon affecting nearly all cell types which harm several macromolecules including DNA, proteins, and fatty acids [1,2]. This kind of damage results largely from reactive oxygen species (ROS) generation that can be produced in a number of ways, from exposition to metal/metalloids [3][4][5] and to their normal formation during respiration in aerobes [6] and as part of the cellular immune response in humans [7], among others. Since the overall ROS effect on bacteria is not fully understood, it is tempting to focus on unexplored approaches. In this context, the oxidation of particular cell components-in addition to the direct damage they suffer-results in the formation of several toxic byproducts such as ROS-derived aldehydes. In eukaryotic cells, aldehyde generation comes mainly from the oxidation of membrane polyunsaturated fatty acids (PUFAs); initially formed lipid peroxides can then be decomposed to different reactive aldehydes that in turn cause damage to different cellular components [8].
Although oxidative stress effects on Escherichia coli have been widely analyzed [6], the formation of ROS-derived aldehydes has not been particularly considered in this bacterium. The little available evidence comes from the E. coli aldehyde reductase YqhD, an enzyme whose activity confers resistance to several oxidative stress elicitors by decreasing aldehydemediated cell damage [5]. Since PUFAs are absent from the E. coli membrane [9], it seems unlikely that these molecules could represent the aldehyde source in this bacterium. In contrast, monounsaturated fatty acids (MUFAs) do exist in E. coli [9] which seem to be good candidates for aldehyde production as they can be oxidized to form lipid peroxides [10][11][12]. This assumption is supported by observations pointing out that the E. coli resistance to several oxidative stress elicitors is dependent on membrane MUFA composition [13]. In this work, aldehyde generation was found to occur in E. coli under toxicant-induced oxidative stress conditions which are dependent on the membrane MUFA ratio. In addition, it also results in modulating lipid-derived peroxide levels, oxidized proteins, and E. coli resistance to oxidative stress elicitors.

Aldehyde Content Determination.
Cell cultures (500 mL, OD 600 ∼0.3) were induced with 0.02% arabinose for 2 h and exposed to 0.25 M TeO 3 2− , 0.3 mM H 2 O 2 , or 0.015 mM tertbutyl hydroperoxide (TBH) for 30 min. After washing with 10 mM potassium phosphate buffer pH 7.0 (buffer A), cells were suspended in 500 L of buffer A, mixed with 500 L of cyclohexanedione reagent [(ammonium acetate (10 g), acetic acid (10 mL), and 1,3-cyclohexanedione (0.25 g) in 100 mL of mili-Q water)], and incubated at 60 ∘ C for 1 h. After centrifuging at 5000 × g for 10 min, the pellet was discarded, and aldehyde adducts were concentrated in a Sep-pak C18 (Waters) column. After washing with 3 mL of mili-Q water, adducts were eluted with 1 mL of HPLC-grade methanol. The alcohol was evaporated in a SpeedVac apparatus and the sample washed with 500 L of chloroform, centrifuged to precipitate any remaining salt, and evaporated. Adducts were suspended in 50 L of methanol : H 2 O (1 : 1), and 20 L of the mixture was injected in a C18 HPLC column (Agilent) along with 2.5 moles of octanal as internal standard. The  (MIC). Cells from overnight cultures were diluted 100-fold with fresh medium, grown to OD 600 ∼0.3, and 10 L aliquots were inoculated into 96-well plates containing serial dilutions of the particular toxicant in 150 L of antibiotic-amended medium and plates were incubated for 48 h at 37 ∘ C with gentle shaking. ROS elicitors tested included the superoxidegenerating compound tellurite [5], the lipid-peroxidating agent TBH [15] and hydrogen peroxide [6].

Protein Carbonylation.
Protein carbonyl group content was determined as described earlier [16,17]. Briefly, nucleic acids-free cell extracts (100 L) from E. coli BW25113 ΔyqhD exposed to the toxicants were mixed with 4 volumes of 2 M HCl containing 10 mM dinitrophenylhydrazine and incubated for 1 h at room temperature with vortexing every 15 min. Proteins were precipitated with 1 volume of trichloroacetic acid (20%) and pelleted at 10000 ×g for 10 min. After washing 3 times with ethanol : ethyl acetate (1 : 1), the pellet was dissolved with 450 L of 6 M guanidine hydrochloride containing 50 mM dithiothreitol. Carbonyl content was determined at 370 nm using a molar absorption coefficient of 22,000 M −1 cm −1 [18].

Fatty Acid Profile Determination.
Bacterial cultures (50 mL) were exposed for 30 min to the toxicants, sedimented, and dehydrated in a SpeedVac equipment. Pellets were suspended in 500 L of methanolic HCl (5%) and incubated at 80 ∘ C for 10 min to produce fatty acid-derived methyl esters (FAMEs). Resulting mixtures were extracted with hexane (500 L) and evaporated to a volume of 50 L. Five L of each sample were injected in a diphenyl-dimethylsiloxane (5 : 95%) column (PTE-5 Supelco) and fractionated in a Perkin Elmer autosystem gas chromatograph apparatus.

Lipid Peroxide Content Determination.
Lipid peroxidation levels were assessed using the ferrous oxidation/xylenol orange (FOX) assay [19] with some modifications. Briefly, 50 mg of fresh E. coli ΔyqhD cells were suspended in 500 L of 50 mM Tris-HCl (pH 7.4) buffer, disrupted by sonication, and centrifuged at 10000 ×g for 10 min. Both crude extracts and pellets were sonicated again, this time in the presence of 1% SDS. Lipids were extracted twice with 1 volume of methanol : chloroform (1 : 2 v/v). The organic phase was rescued, evaporated in a SpeedVac, and suspended in 1 mL of the FOX reagent. After 1 h at room temperature, the lipid peroxide content was determined at 560 nm. Results were expressed as hydrogen peroxide equivalents.

Aldehyde Generation in Stressed E. coli.
It was previously established that E. coli lipid peroxidation levels are dependent on the membrane MUFAs ratio [13] and that peroxides derived from pure MUFA can be decomposed to aldehydes [11]. In this context, this work focused on evaluating the production of these reactive compounds in E. coli under oxidative stress conditions. To asses this, an aldehyde-specific HPLC fluorometric determination procedure [20] was used along with an E. coli strain lacking the YqhD aldehyde reductase [21] to facilitate aldehyde detection. Under normal growth conditions, an aldehyde species eluting at ∼16 min (Figure 1(a)) was detected. Exposure of E. coli ΔyqhD to the oxidative stress elicitors TeO 3 2− , H 2 O 2 , or TBH resulted in increased aldehyde levels (Figure 1(b)). Interestingly this aldehyde was detected even in unstressed conditions ( Figure 1(b), control), showing that its generation occurs in metabolically active E. coli.

Oxidative Stress Effects on the E. coli Membrane MUFAs.
Given the link between lipid peroxidation and aldehyde generation [10,11] and the relationship MUFA content/lipid peroxidation previously reported [13], it is likely that MUFA → lipid peroxidation → aldehyde generation pathway takes place. To evaluate this putative relationship, the MUFA ratio (MUFA/total membrane fatty acids) was determined by gas chromatography (GC) in cells exposed or not to stress elicitors. As expected, decreased MUFA content (palmitoleic + vaccenic acid, C16 : 1 + C18 : 1) was observed under oxidative stress conditions (Figure 2(a)).
The fact that aldehyde levels increase while MUFAs ratio drops in ROS elicitors-exposed cells supports the idea of a link between them. In this context, lipid peroxide levels in membrane extracts from stressed E. coli were evaluated using the FOX assay as described in Materials and Methods. In this line and as previously stated in E. coli BW25113 [13], increased levels of lipid peroxidation were observed upon exposition of E. coli ΔyqhD to oxidative stress elicitors (Figure 3(a), control). These results are consistent with MUFAs being putative substrates for membrane lipid peroxidation.

Effect of Modulating MUFAs Ratio on Lipid Peroxidation.
To further establish the link MUFA → lipid peroxidation, the effect of changing the membrane MUFA ratio in cells facing oxidative stress was evaluated. To achieve this, fabA and cfa genes, whose products are involved in the synthesis or modification of monounsaturated fatty acids [22,23], were overexpressed in E. coli ΔyqhD. Mutants lacking these genes are unviable unless cultures are amended with the appropriate fatty acids [24]. Overexpression of fabA or cfa results in changes in the fatty acid ratio of almost all fatty acids present in the E. coli membrane. Upon cfa overexpression Octanal was used as an internal standard (peak at 20 min). (b) 16 min eluting aldehyde species variation. Cells were exposed to the indicated toxicants for 30 min in minimal VB medium and used for determining aldehyde levels as described in Section 2. Error bars represent SD ( = 5). Asterisks indicate significant difference, < 0.05.
the observed decrease of the unsaturated fatty acids ratio was particularly interesting (Table 1, C16 : 1 + C18 : 1). When cells were exposed to oxidative stress elicitors, MUFA proportions decreased (∼10%) in the control, parental strain, and to a lesser extent in fabA-expressing E. coli (Figures 2(a) and 2(b)). No information could be obtained when analyzing cfa-expressing cells since the MUFA levels were so low that fell close to the experimental error (Figure 2(c)).
To get a closer picture of MUFA content/aldehyde generation, lipid peroxidation levels were assessed in strains with artificially altered MUFA content. In the presence of stress elicitors, decreased lipid peroxide levels were found in strains  Figure 3: Membrane peroxide assessment in stressed E. coli BW25113 ΔyqhD. Cells carrying pBAD, pfabA, or pcfa were exposed to the indicated toxicants for 30 min in minimal VB medium and used for determining lipid peroxides as described in Section 2. Error bars represent SD ( = 5). Asterisks indicate significant difference, < 0.05. exhibiting lower MUFA ratios (Figures 3(b) and 3(c)) than those observed in the parental strain (Figure 3(a)).
As these results suggested a direct relationship between MUFA content and lipid peroxidation, the next step was to assess aldehyde generation in strains containing decreased MUFA ratios. As expected, in the presence of stress elicitors, cells expressing fabA or cfa (Figures 4(b) and 4(c)) showed lower aldehyde levels than the parental strain (Figure 4(a)).

Effects of MUFAs Modulation on Intracellular Oxidative
Damage. Given that lipid peroxidation generates byproducts that may cause secondary damage to several macromolecules [25], protein carbonylation (a kind of damage normally mediated by aldehydes and other oxidative agents) [26] was assessed in stressed cells. While in the parental, untreated strain carbonyl group levels were rather unchanged, fabA and cfa over expression resulted in decreased protein oxidation mainly in tellurite-treated cells ( Figure 5).

Effects of MUFAs Modulation on Toxicant's Minimal Inhibitory Concentrations.
Since altering MUFA ratios could affect the level of ROS-mediated cell damage, the overall cell response to stress elicitors could be affected as well. In this line, resistance to the tested toxicants was assessed by determining their minimal inhibitory concentrations (MICs). When MUFA ratios decreased by 40% or 90% (pfabA and pcfA, resp.) (Table 1), tellurite resistance increased twofold. Upon fabA or cfA over expression resistance to hydrogen peroxide and TBH increased two-and fourfold, respectively, showing a link between MUFAs content and resistance to oxidative stress elicitors ( Table 2).

Aldehyde Identification.
To establish that the aldehyde species eluting at 16 min (Figure 1(a)) comes from MUFAderived lipid peroxides, its identity was assessed by mass spectrometry. Figure 6(a) shows the mass spectra for the derivatized aldehyde, whose highest m/z value was 349 (Figure 6(a)). The most reasonable fit to this spectrum corresponds to the pseudomolecular m/z signal expected for the 1,3 cyclohexanedione derivate [20] of 4-hydroxy 2-nonenal ( Figure 6(b)).

Discussion
A previous work from our group indicated that aldehyde detoxification plays a role in resistance to oxidative stress [21]. In this context, the finding of an aldehyde species produced Total fatty acids from the indicated E. coli strains were subjected to direct transesterification and analyzed by gas chromatography. Results are expressed as the percentage of total fatty acids. C16 : 1, palmitoleic acid; C16, palmitic acid; C17: margaric acid; C18 : 1, vaccenic acid; C16 : 1 + C18 : 1, and variation of total MUFA content (C16 : 1 + C18 : 1); C19: nonadecylic acid.
Aldehyde levels (%) * *  Figure 4: Aldehyde generation in E. coli exposed to oxidative stress. E. coli cells containing pBAD, pfabA, or pcfa were exposed to the indicated toxicants for 30 min in VB medium and used for determining aldehyde levels as described in Section 2. Error bars represent SD ( = 5). Asterisks indicate significant difference, < 0.05. : Protein carbonylation in E. coli exposed to different toxicants. Cells carrying pBAD, pfabA, or pcfa were exposed to the indicated oxidative stress elicitors for 30 min in VB minimal media, and carbonyl groups were assessed using 2,4 DNPH as indicated in Section 2. Error bars represent SD ( = 5). Asterisks indicate significant difference, < 0.05.
in unstressed conditions but whose levels increase under oxidative stress conditions ( Figure 1) suggested both that its generation results from the normal, aerobic metabolism in E. coli [11,13] and that it is dependent on the cell oxidative status. Considering the proposed MUFA → lipid peroxidation → aldehyde generation pathway, the observed decrease of MUFAs levels (Figure 2(a)) and increased amounts of lipid peroxidation (Figure 3(a)) are consistent with MUFAs being substrates for membrane lipid peroxidation, with the observed augment of aldehyde levels coming most probably from lipid peroxide decomposition. Furthermore, upon MUFA ratio modulation decreased levels of lipid peroxidation (Figures 3(b) and 3(c)) and aldehyde (Figures 4(b) and 4(c)) were observed when cells were exposed to oxidative stress elicitors, supporting the idea of a direct link MUFA → lipid peroxidation → aldehyde generation. Oxidized by ROS, monounsaturated fatty acids (palmitoleic, vaccenic) would generate lipid peroxides in the same manner as oleic acid (MUFA) is oxidized to form hydroperoxides which finally decompose to reactive aldehydes [11]. Thus, the lower the MUFA content, the lower the lipid peroxidation level and aldehyde generation.
On the other hand, one noteworthy aspect of the MUFA → lipid peroxidation → aldehyde generation link is represented by the impact of MUFA ratio modulation on oxidative damage within the cell, particularly by cell exposition to tellurite ( Figure 5). This result is intriguing since previous findings indicated that the observed effects were independent of the toxicant. In this context and given that peroxides pass freely through the cell membrane [6], it is conceivable that shortly after toxicant exposure they could affect all cell components rather than exclusively the membrane. This may possibly make peroxide-mediated protein carbonylation less dependent on products derived from membrane oxidation. On the other hand, when compared to TBH and H 2 O 2 , the intimate interaction of tellurite with the E. coli membrane [27] could result in a localized effect that may enhance any damage derived from membrane oxidation byproducts. These results suggest that the E. coli membrane composition is relevant regarding the extent of cell damage caused by oxidative stress elicitors. Similar results of damage by membranederived byproducts such as peroxides and/or aldehydes have been observed in other organisms [8,28]. Given the observed inverse relationship between MUFA content and resistance to ROS elicitors (Table 2), the relevance of the E. coli membrane composition also seems to be relevant to the bacterial resistance towards oxidative stress. Interestingly, cells exposed to NiCl 2 , a toxicant that does not produce oxidative damage, exhibited no differences in resistance levels compared with untreated controls (data not shown). These results are in agreement with those of Pesakhov et al. [29], who observed enhanced resistance to oxidative stress upon MUFA depletion from the E. coli membrane. Due to the potential effects of MUFA ratio alterations on membrane fluidity, we cannot fully disregard a variation in toxicant access through the membrane. However this seems rather unlikely because NiCl 2 toxicity is not affected by MUFA ratio variations. Since lipid peroxide and aldehyde detoxification systems seem to be part of the E. coli response to oxidative stress elicitors [5,30,31], the observed increase in resistance to these agents could be more likely related to decreased lipid peroxide and aldehyde levels.
Finally, the identity of the detected aldehyde also suggests an MUFA-derived origin for this compound. Based on the published models for aldehyde generation from oleic acid [11], a mechanism that could explain the generation of 4-hydroxy 2-nonenal is proposed; this aldehyde might derive from the autooxidation of 10-and/or 13-vaccenic acid hydroperoxide which in turn could come from vaccenic acid oxidation (see Figure S1 in the Supplementary Material available online at http://dx.doi.org/10.1155/2013/563756). This model is in agreement with the results showing decreased MUFA ratios in fabA-and cfa-expressing cells, where a preferential decrease of the vaccenic acid content was observed ( Table 1). The autooxidation step in the proposed model is supported by former evidence indicating that aerobic conditions are required for aldehyde production [21] and for autooxidation to occur [32].

Conclusion
Our results show that oxidative stress elicitors affect the E. coli membrane MUFA ratio. The production of an aldehyde derived from these fatty acids-most likely 4-hydroxy 2nonenal-increases upon toxicant exposure. Finally, a direct relationship between membrane MUFAs and the generation of lipid peroxides and reactive aldehydes was found, which seems to modulate-at least in part-the cell's tolerance to oxidative stress elicitors.


extfieldsofstudy: Biology Medicine

text:
Aberrant MicroRNA Expression in Endometrial Carcinoma Using Formalin-Fixed Paraffin-Embedded (FFPE) Tissues

This study aimed to identify the candidate miRNAs in the carcinogenesis of endometrial carcinoma, and to explore whether FFPE material would be suitable for miRNA profiling. We identified the differences between miRNA expression profiles using human miRNA microarray in endometrioid endometrial adenocarcinomas (EECs) and normal endometria. Of those tested, miR-200a*, miR-200b*, miR-141, miR-182, and miR-205 were greatly enriched. The expressions of these five miRNAs were validated using quantitative real-time reverse transcription-PCR (qRT-PCR). We then performed qRT-PCR miR expression profiling in 30 FFPE specimens (20 EECs, 10 normal endometria) and re-confirmed the results of differential expression between cancer and normal tissue. Following this, we tested whether the specific inhibition of overexpressed miRNAs would alter chemosensitivity. In the in vitro cell viability assay, anti-miR200b* showed a trend toward enhanced cytotoxicity slightly in cisplatin compared to the negative control (p = 0.07). This information provided the candidate miRNAs for further confirmation of the role of miRNAs in the carcinogenesis of EECs, potentially serving as a diagnostic or therapeutic tool. FFPE specimens of endometrial tissues are suitable as a source for miRNA microarray profiling.

Introduction
MicroRNAs (miRNAs) are small non-coding RNAs of [19][20][21][22][23][24] nucleotides that regulate gene expression post-transcriptionally by imperfect base-pairing to messenger RNAs [1]. Hundreds of miRNAs have been identified in various animal genomes. Each miRNA is believed to target as many as two hundred transcripts and approximately 30% of human genes are regulated by miRNAs [2]. The biological functions of most miRNAs are not fully understood. However, it has been suggested that miRNAs are involved in various biological processes, including cell proliferation, apoptosis, differentiation, and metabolism [3,4]. Since the discovery in 2002 that miRNA dysregulation is linked to cancer, [5] many studies have sought to describe the relationship between miRNAs, cancer progression, and metastasis [6].
Endometrial carcinoma is the most common gynecologic malignancy in Western countries and the fourth most common cancer among women worldwide [7,8]. Endometrioid adenocarcinoma is the main form of endometrial carcinoma, accounting for 75-80% of cases [9]. Although focusing on unopposed estrogen stimulation of the endometrium to carcinogenesis has already yielded much information, the detailed network of events leading from estrogen stimulation to tumor development has not been clarified. Some studies have shown that ovarian steroids can influence the expression of miRNAs in the endometrium and carcinogenesis of endometrial cancer is considered to be related to the progressive accumulation of multiple genetic abnormalities, which may activate oncogenes and inactivate tumor suppressor genes [10,11]. Therefore, miRNAs may play an important role in the carcinogenesis of endometrial carcinoma.
While studies on miRNAs so far have tended to focus on freshfrozen (FF) tissues, other types of samples, such as formalin-fixed paraffin-embedded (FFPE) samples, are being explored [12,13]. FFPE samples have significant value as they are often the only source of tissue available from large patient cohorts with comprehensive clinical data and long-term follow-up. With this in mind, we present the results of miRNA deregulation in a set of endometrioid endometrial cancer (EEC) and normal endometrial tissues from both FF and FFPE samples using real-time quantitative PCR array.

Patients and tissue specimens
Fresh-frozen biopsy specimens from patients with EECs (n = 4) and normal endometrial specimens from patients who underwent a hysterectomy to treat other benign disease (n = 4) were collected. After surgical removal, the tissues were frozen immediately in liquid nitrogen and stored at 280uC. FFPE tissues were also obtained from the hysterectomy specimens of 20 endometrial cancer patients, as well as 10 normal endometrial tissues from endometrial curettage specimens. Ethical approval was obtained from the institutional review board of Seoul Metropolitan Government Seoul National University Boramae Medical Center for this study and written informed consent was obtained from all patients who provided tissues used in this study.

RNA isolation and gene expression profiling
In this study, we performed global miRNA gene expression analyses using Agilent Human miRNA Microarray Version 3 (Agilent design IDs 021827), including 866 human and 89 human viral miRNAs. The sample preparation was performed according to the instructions and recommendations of the manufacturer. Total RNA was isolated using Trizol, as described by the manufacturer (Ambion). RNA quality was assessed by Agilent 2100 Bioanalyzer using the RNA 6000 Nano Chip (Agilent Technologies, Amstelveen, the Netherlands) and quantity was determined by ND-1000 Spectrophotometer (NanoDrop Technologies, Inc., DE, USA).
For each RNA sample, 100 ng of total RNA was used as input into the labeling reaction and the labeled miRNA was hybridized to the array for 20 hours at 55uC and 20 rpm, as recommended in the protocol (miRNA Microarray System with miRNA Complete Labeling and Hyb Kit protocol 2.1). After hybridization, the chips were washed and scanned using an Agilent DNA Microarray Scanner.
The microarray data was analyzed using SAM software version 3.08 to select the differentially expressed miRNAs. The main benefit of the SAM approach is the computation of the false discovery rate (FDR). The FDR represents the percentage of genes identified as significant by chance. A low FDR for a significant gene would indicate a greater likelihood that the gene represents a true, significant gene, rather than a falsely discovered one.

Data analysis for microarray
Three normalization methods (total intensity, global median, and cross-correlation) were used to identify the best method for correcting systematic biases in the array data. Differential expression of miRNA gene selection was performed using the Significance Analysis of Microarrays (SAM, Stanford, California, USA) approach (Thomson et al., 2004). Hierarchical clustering was performed using Cluster 3.0 software (Stanford, California, USA) to assess expression trend.

Real-time RT-PCR
To validate the results of miRNA array, the five most differentially expressed miRNAs were subjected to real-time RT-PCR. The cDNA was synthesized from the miRNA using a Mir-X miRNA First-strand Synthesis and SYBR qRT-PCR Kit (Takara Bio Inc). Quantitative real-time PCR with a Takara Thermal Cycler Dice (TP800)H used primers and templates mixed with the SYBR Premix. The sequence of the miRNA primer was designed based on miRBase (http://www.mirbase.org). Primer sets for individual miRNAs are listed in Table 1. These primers were prevalidated to generate single amplicons. DNA was amplified for 40 cycles of denaturation for 5 s at 95uC and annealing for 20 s at 60uC. The data generated from each PCR reaction was analyzed using the Thermal Cycler Dice Real Time System ver 2.10 B (Takara Bio Inc.) software package. We used small nucleolar RNA U6 (Ambion, Austin, Texas, USA) as an internal control and the expression of miRNAs was quantified as DCt values, where Ct = cycle threshold, DCt = (Ct target miRNAs 2 Ct u6). DCt was calculated using RQ manager software, version 1.2 (Applied Biosystems).

qRT-PCR for formalin-fixed paraffin-embedded (FFPE) tissues
To generalize the results of differential expression between cancer and normal tissue, and to determine whether miR analysis of FFPE tissues of endometrial cancer is feasible, quantitative realtime PCR (qRT-PCR) miRNA expression profiling was performed in 30 archival FFPE specimens (20 cases of endometrioid adenocarcinoma described in Table 2 and 10 normal endometria obtained from office-based biopsy for benign disease). FFPE tissues blocks were sectioned at 10 mm and evaluated by a pathologist. Regions of invasive carcinoma were confirmed and marked on each slide. Marked regions were microdissected using a new, sterile, disposable scalpel blade and the dissected tissue placed immediately into a labeled RNase-free microcentrifuge tube with a closed cap. For the 10 normal endometrial tissues from the office-based biopsy, each thin, curled-up tissue strip was placed directly into the tube and microdissection was not required.
Total RNA was extracted using Recoverall (Ambion, Austin, TX, USA), according to the manufacturer's instructions. Xylene was added to the FFPE samples briefly to remove paraffin. The tissues were then digested with protease and treated with DNase. After washing, the RNA, including the small miRNA fraction, was eluted with distilled water. The concentrations and quality of the RNA recovered were measured using the Nanodrop 1000 A spectrophotometer (

Cell lines and transfection of anti-miR
The human endometrial cancer cell lines, Hec1A and Ishikawa were obtained from ATCC (American Type Culture Collection, Manassas, VA, USA) and ECACC (European Collection of Cell Cultures, Wiltshire, UK), respectively. Both cell lines were prepared as follows: Hec1A cells were grown at 37uC in 5% CO2 in RPMI 1640 supplemented with 15% fetal bovine serum, penicillin (100 units/ml), and streptomycin (100 Ag/ml); and Ishikawa cells were maintained in Dulbecco's Modified Eagle's Medium/Ham's Nutrient Mixture F-12 (DMEM/F12).
The miR-inhibitor solutions (0, 25, 50 nM) (Ambion, Austin, TX, USA) were stocked briefly in a 50 ml RNase-free, pH 7.4buffered solution. 2 ml of G-fectin reagent (Genolution Pharmaceuticals) were then added and the solutions incubated for 10 minutes at room temperature. The cells were split and 450 ml of media with cells were added to 96-well plates with 30-50% cell confluency for optimum transfection efficacy. After 10 minutes, lipoplex was added to each intended plate. Assays was performed 24,48 hours after transfection. To further assess whether the miR inhibitors affected the cytotoxic effect of chemotherapeutic agents, we treated the transfected cells with cisplatin and paclitaxel.
Cell viability was monitored using the 2-(4,5-dimethyltriazol-2yl)-2,5-diphenyltetrazolium bromide (MTT, Sigma, St. Louis, MO, USA) colormetric assay; 5 mg/ml of MTT solution were added to each well. After four hours of incubation at 37uC, the cell supernatants were not discarded. MTT crystals were dissolved with DMSO and the absorbance measured at 570 nm. All experiments were conducted with 24 wells per experiment and repeated at least three times.

Statistical analysis
Statistical analysis was performed using Statistical Package for Social Sciences (SPSS) software 18.0 (SPSS, Inc., an IBM Company, Chicago, Illinois, USA). The Mann-Whitney test was used to analyze the differences in miRNA expression between the tumor and non-tumor tissues. A p-value calculated by one-tailed test of less than 0.05 was considered statistically significant.

Distinct miRNA signatures in microarray
We analyzed the miRNA expression profiles of four endometrioid adenocarcinoma and four normal endometrial tissues using a two-color system. When the selective conditions were a FDR of less than 0.05 and the fold change was 2.87, there were eight human miRNA genes up-regulated and 49 down-regulated by SAM analysis (Fig. 1). The hierarchical clustering was performed after SAM analysis (Fig. 2). The up-regulated miRNA was miR-200a* miR-205, miR-141*, miR-200b*, miR-141, miR-200b, miR-200a, miR182. Among these miRNAs, five were upregulated in tumor samples where the fold change was more than 5-fold (miR-200a*, miR-205, miR-141*, miR-200b*, miR182).

Validation of the microarray results with cell lines, FF, and FFPE tissues
Five miRNA genes (miR-200a*, miR-205, miR-141*, miR-200b*, miR182) were selected because of their notably high differential expression in tumor tissues in the microarray data. The expression of the five miRNA genes was determined using realtime PCR analysis.
In line with the microarray results, the expression levels of the five miRNAs were much higher in endometrial cancer tissues and endometrial cancer cell lines (Hec1A, Ishikawa) than in non-tumor tissues. (Fig. 3) To generalize the above results and examine whether the miRNA sequencing could be applied to FFPE-derived samples, we investigated the expressions of three miRNAs (miR-141*, miR-205, miR182) using 20 microdissected FFPE endometrial cancer samples and 10 non-tumor endometrial FFPE tissues. The miR-200 family and miR-141 are known to have similar seed sequences, meaning that it is highly probable that they share target genes. Therefore, we selected only miR-141 (instead of miR-200a* or 200b*) for the validation study with FFPE-derived tissues. The altered expressions of all three miRNAs between tumor and benign samples were highly consistent with the data from the fresh-frozen tissues (Fig. 4).

Relationship between miRNA expressions and various clinicopathologic factors
In total, 20 microdissected FFPE samples of endometrioid carcinoma were used to investigate the relationships between overexpressed miRNAs and a variety of prognostic factors including age, tumor grade, and lymph node metastasis. As shown in Table 3, we found no statistically significant correlation between DCt value of miRNAs and the prognostic factors.

Cell viability assay
To investigate the cellular mechanism for the hypothesis that high miRNA expression is associated with tumor cell progression, we transfected the three miR inhibitors (miR-141*, miR-205, miR-182) into the endometrial cancer cells (Hec1A) to downregulate miRNA activity. After 72 hours of incubation in the 25 nM and 50 nM miR-inhibitor concentrations, cell proliferation was not inhibited by any miR-inhibitor in the MTT assay. (Fig. 5).

Effect of specific inhibition with anti-miRNAs on chemosensitivity
To address the hypothesis that miR overexpression is involved   in chemosensitivity, we tested whether the specific inhibition of overexpressed miRNAs alters the sensitivity of cells to cisplatin or paclitaxel. We transfected with the five anti-miRNAs (anti-miR-141*, anti-miR-205, anti-miR-182, anti-miR-200a*, anti-miR-200b*) into the Hec1A cells and treated them with IC50 of cisplatin or paclitaxel for 48 hours. As shown in Fig. 6, anti-miR200b* showed a trend toward enhanced cytotoxicity in cisplatin compared to the negative control in three repeated experiments (p = 0.07). However, it did not show any effect on the cytotoxicity of paclitaxel.

Discussion
In this study, we identified several altered miRNAs expressions in endometrial cancer tissues and normal endometrial tissues.
Our data shows some similarity with previously published reports. The up-regulation of the miR-200 family (miR-141, 200a, 200b) is observed consistently, despite the use of different patient populations and different tissue types (fresh vs. formalin-fixed) in EEC relative to normal controls [14][15][16][17][18].
This miR-200 family is composed of five miRNAs localized on two genomic clusters: miR-200c and miR-141 on chromosome 12 and miR-200a, miR-200b and miR-429 on chromosome 1.  Members of this family are known to be involved in the epithelial to mesenchymal transition (EMT) that occurs during tumor invasion and metastasis in uterine and other tissues [19]. Coordinately regulated with the miR-200 family, miR-205 is one of the consistently over-expressed miRNAs in EEC. Although our data did not include the data associated with the correlation between overexpressed miRNAs and clinical prognostic factors due to the limited case number and recurrent cases, the aberrant expression of miR-205 was reported to be correlated with advanced-stage disease and poor patient survival rates in endometrial cancer [15,20].
Up-regulated miR-182 in endometrial cancer is reported to be associated with the repressing FOXO1 gene, which is known to be down-regulated in endometrial cancer compared to normal endometrial [21,22]. The ability of miR-182 to promote FOXO1 repression may adopt a key role in endometrial tumorigenesis by bypassing the cell cycle and cell death control.
It is standard practice for pathology departments to store almost all human samples in FFPE blocks; these can be linked with clinical databases, including disease diagnoses and patient followup information. The use of FFPE samples is always challenging but is extremely beneficial, as it is almost the only way to make large-scale and clinical trial/cohort-based studies possible. In recent years, FFPE specimens have been used for real-time PCRbased quantitative miRNA expression studies [23][24][25]. Since these samples are assumed to have insufficient quality and integrity of RNA, they have not been used for whole-genome, small, noncoding RNA sequencing analysis to characterize miRNA expression. In our study, miRNAs could be detected in both frozen and FFPE samples. We also found that miRNAs are relatively stable in FFPE samples even in the curettage specimens collected on an outpatient-basis. One hypothesis is that they are too small to be degraded [25,26]; however, this hypothesis has not been supported by any reported data. As we now know, active, mature miRNAs are processed and function via binding to Argonaute family proteins [27,28]. These protein-miRNA complexes may protect the functional population of miRNA from degradation, especially during the process of formalin fixation and storage in paraffin. The anticipated benefits of using FFPE in miRNA work on endometrial cancer are: first, it is almost the only way to make large-scale and clinical trial/cohort-based studies possible; second, by using microdissection of FFPE tissues we can exclude the possibility of contamination of normal endometrial tissues, which can happen during the intraoperative collection of endometrial tumor tissues; and third, the stored endometrial tissues can be obtained easily via office-based biopsy. The future miRNA work with office based endometrial tissues may provide a basis to actualize preoperative prediction of prognosis or response for treatment.
The miR-200 family is expressed more highly in endometrial cancers than in normal endometrial tissues, and its overexpression is known to be correlated with cisplatin resistance [29][30][31]. Although we were unable to document whether the highly expressed miRNAs have an impact on cellular proliferation or apoptosis by using endometrial cancer cell lines, we identified that treatment with anti-miR200b* showed a trend toward enhanced cytotoxicity of cisplatin although we did not get statistical significance. Although not consistent, the association between the aberrant expression of miR200b and the change of response to cisplatin has been documented by other studies and we obtained similar results to those in previous reports [32,33].
The major limitation of this study is the lack of prediction and identification of an exact target for the miRNAs validated in this study. Future research is needed to resolve these problems. If the target genes of these miRNAs are identified, the role of differential expression of the miRNAs in the carcinogenesis of endometrioid adenocarcinoma will be clarified. Another limitation is that we were unable to document the correlation between aberrant expression and the prognostic factor because of the small sample size and limited number of recurrence cases.
In summary, this study focuses on investigating the relative expression of mature miRNA genes in endometrioid adenocarcinoma and identifying a specific miRNA expression profile. We also tested whether FFPE material is suitable for miRNA profiling and obtained satisfactory results. Despite the uncertainty regarding the functional effects of these miRNAs, the miRNA expression profile may provide a basis for further study of the miRNA function in endometrioid adenocarcinoma, and be used as a prognostic marker for the aggressiveness of human cancer.


extfieldsofstudy: Medicine Biology

text:
The quantitative proteomic response of Synechocystis sp. PCC6803 to phosphate acclimation

Background Inorganic phosphate (Pi) is a critical nutrient for all life and is periodically limiting in marine and freshwater provinces, yet little is understood how organisms acclimate to fluctuations in Pi within their environment. To investigate whole cell adaptation, we grew Synechocystis sp. PCC6803, a model freshwater cyanobacterium, in 3%, and 0.3% inorganic phosphate (Pi) media. The cells were allowed to acclimate over 60 days, and cells were harvested for quantitative high throughput mass spectrometry-based proteomics using the iTRAQ™ labelling technology. Results In total, 120 proteins were identified, and 52 proteins were considered differentially abundant compared to the control. Alkaline phosphatase (APase) activities correlated significantly (p < 0.05) with observed relative PhoA abundances. PstS1 and PstS2 were both observed, yet PstS1 was not differentially more abundant than the control. Phycobilisome protein abundances appeared to be coordinated, and are significantly less abundant in 0.3% Pi than 3% Pi cultures. Also, the central metabolic cell function appears to have shifted towards the production of (NADPH) reducing energy and nucleotide sugars. Conclusions This acclimation response bears strong similarity to the previously reported response to nitrogen deprivation within Synechocystis sp. PCC 6803. However, it also demonstrates some characteristics of desiccation stress, such as the regulation of fatty acids and increased abundance of rehydrin in the 3% Pi culture.

Background
Cyanobacteria comprise one of the largest groups of prokaryotes. They are found in a wide variety of niches, including terrestrial and hypersaline environments, and in oceans, lakes and rivers. Synechocystis sp. PCC 6803 (hereafter Synechocystis), a model freshwater cyanobacterium, has strong potential biotechnology applications in areas as diverse as biofuels [1], biopolymers [2] and other secondary metabolites [3]. Due to this biotechnological interest, its general applicability as a model organism for CO 2 fixation and environmental stress responses has been the subject of post-genomic investigations [4][5][6][7][8], including proteomics investigations using both 2-DE [8] and shotgun proteomics workflows [7].
For most microorganisms, the preferred source of the essential nutrient phosphorus is inorganic phosphate (P i ). However, phosphate is the planet's least abundant naturally occurring mineral [9]. P i limitation occurs for sustained periods in many geographically dispersed freshwater lakes and marine sites. To date, however, there have been relatively few investigations into the cell-wide response of microorganisms to this form of nutrient stress, particularly over longer periods that reflect adaptation rather than short-term response. An understanding of these processes will be of use not only in the basic understanding of microbes and the niches they occupy, but could also be applied to develop biomarkers to follow stages in the phosphorus biogeochemical cycle within aquatic environments. In addition, the identification of novel proteins associated with P i uptake could be exploited in the removal of P i for water quality improvement, whilst enzymes involved in the catabolism of organophosphorus molecules are of interest in the pharmaceutical and agribiotech industrial sectors.
There has been a range of phosphate starvation and limitation studies in bacteria carried out through cDNA microarrays to investigate global transcriptome changes [10][11][12][13] and qualitative overview analysis using 2-DE workflows to study broad proteome changes [14][15][16][17]. To date, there have only been two high-throughput quantitative proteomic assays of P i limitation in cyanobacteria, focusing on the marine species Prochlorococcus [18,19]. While it is tempting to compare the observations obtained from these studies, comparison among datasets has also been further complicated by the different types of experiments conducted, which range from evaluation of the short-term responses to starvation conditions (shift to P-free medium) to studies of adaptation to P i limitation. However, one of the most common observations in all of these studies is the up-regulation of pho regulon genes, as seen in studies conducted on Bacillus subtilis [15], Escherichia coli [19], Prochlorococcus spp. [13,18,19], Synechococcus WH8102 [20] and Corynebacterium glutamicum [21].
Unlike other prokaryotic systems, reports on P i limitation responses in cyanobacteria are relatively few. When available, these studies consist more generally of shortterm P i shock experiments with a shift from replete to P i free medium [10,13,20,[22][23][24][25][26]. However, these studies have revealed that the phosphate-sensing system in Synechocystis is modulated by SphS (sll0337; histidine kinase; analogous to PhoR of E. coli) and SphR (slr0081; response regulator; analogous to PhoB of E. coli) [27], which form a two-component signal transduction system. Also, an in-depth investigation of P i -binding proteins within Synechocystis showed differential regulation, functional roles and P i transport characteristics for its two ABC-type phosphate transporter proteins, PstS1 and PstS2 [22].
Inactivation of phoU, one of the genes encoding phosphate-specific transport system regulatory proteins, caused an increase in both inorganic phosphate (Pi) uptake and polyphosphate accumulation rates [27]. It has been shown that under phosphate starvation, the Synechocystis pho regulatory system responds by increasing its transcript abundance by more than 7-fold compared to normal P i replete conditions [10]. It has been suggested that high light levels also triggered the pho regulon, since light accelerated phosphate assimilation despite limited cell capacity to perform the task [28]. Suzuki et al. used DNA microarrays to investigate the Synechocystis phosphate starvation response [10] and found that the genes encoding the ABC-type phosphate transporter (sphX, PstS1 and PstS2 clusters) and extracellular nuclease (nucH) were significantly up-regulated in addition to the alkaline phosphatase (phoA) gene. The gene encoding a periplasmic binding protein (urtA) was down-regulated. In a separate study under similar conditions, significant up-regulation of the genes for inorganic pyrophosphatase (ppa) and exopolyphosphatase (ppx) was observed [29].
The goal of this work was to study the adaptation of Synechocystis to phosphate limitation using a quantitative shotgun proteomics workflow [30,31]. The proteomes of Synechocystis grown in different phosphate concentrations (3% and 0.3% of the non-limiting level in BG-11 medium) were quantitatively measured using iTRAQ reagents. Coupled with enzyme assays, this investigation forms the basis for understanding global cellular responses, such as the central metabolism and biosynthetic pathways, of Synechocystis in phosphatelimited environments. This study is both novel and timely as it specifically deals with an in-depth analysis of P i -depletion over different levels of phosphate, and over a longer timescale, than has been explored by others. The results of this study provide insights into the ways in which cellular processes are directly influenced by ambient phosphorus concentrations.

Growth characteristics
In phosphate-depleted conditions, the growth rate of Synechocystis was significantly impaired (Additional file 1: Figure S1), with noticeable reduction of colour within the flasks (data from observation, image not available). The control culture reached an OD 730 of 7 at the end of the 60-day cultivation, whereas the phosphate-limited cultures only reached a maximum OD 730 of 0.9 (for 3% P i level) and 0.5 (for 0.3% P i level). Their specific growth rates were calculated as 0.20 day -1 for the control culture, 0.012 day -1 for 3% P i culture and 0.002 day -1 for 0.3% P i culture. This impairment in growth with suboptimal P i levels was expected, and agrees with the trend observed for other organisms [21,32,33].

Proteome overview
A total of 120 proteins were identified and quantified with two or more peptides (Additional file 2: Table S1). A quarter of these were associated with central metabolic functions (glycolysis, pentose phosphate pathway, glycogenesis, glyconeogenesis and carbon fixation) (Additional file 1: Figure S2). A significant fraction (19.2%) was associated with uncharacterised and hypothetical proteins, and 21% were associated with photosynthesis. In the study, 13 detected proteins were more abundant in the 3% P i culture, whereas the abundances of 12 proteins were observed to have increased within the 0.3% P i culture (Table 1). Conversely, we observed 13 proteins to be lowered in abundance within the 3% P i culture, while 16 other identified proteins were less abundant in the 0.3% P i culture (Table 1, Figure 1, Additional file 2: Table S1).
It is instructive to observe that cells acclimated to a lower initial phosphate concentration demonstrate a significantly higher fraction of differentially more abundant proteins from almost all categories ( Figure 1), with the exception of proteins associated with the phycobilisomes. These differences suggest a substantial physiological shift within cells in order to maximise P i usage throughout. Indeed, when observing relative abundance levels, the functional categories most broadly affected are metabolism, nutrient acquisition and the proteins of the phycobilisomes ( Figure 1, Table 1).

Nutrient assimilation and regulation
The most commonly reported response to phosphate limitation is an increase in the activity of the periplasmic enzyme alkaline phosphatase [34]. In this study, the alkaline phosphatase activity was observed to increase as the phosphate level decreased, reaching a maximum activity of 60.7 nmol/min · mg in the 0.3% P i culture ( Figure 2, Table 2). No alkaline phosphatase activity was detected in the control culture. This finding corresponds well with alkaline phosphatase activity changes observed in other cyanobacteria (Plectonema boryanum [35] and Aphanizomenon ovalisporum [36]) subjected to longterm phosphate limitation. No acid phosphatase activity was detected in either of the P i -limited cultures by our methods. Ten proteins involved with nutrient acquisition and regulation ( Figure 2A) were quantified. Of these, six of the eight proteins associated with phosphate assimilation and storage were significantly more abundant than in the control ( Figure 2A, Table 1). The alkaline  phosphatase enzyme, PhoA, and the periplasmic phosphate-binding protein, PstS2, were both significantly more abundant in both 3% and 0.3% Pi cultures, whereas inorganic pyrophosphatase (ppa) was significantly more abundant in 3% Pi culture. We have further confidence with PstS2 abundances, as both data points were significant using the Bonferroni correction. As would be expected, there appears to be no significant observations regarding proteins involved with carbon sources (DctP), iron (bfr) and nitrogen metabolism (GlnA, GlnB, and UreA).
Considering both the relative protein abundance of PhoA in the 100%, 3% and 0.3% P i cultures, and observed APase activity ( Figure 2B, Table 2), there is a direct correlation (p < 0.05, where polynomial regressions fitted both datasets with R 2 values > 0.99, and APase activity is approximately 22.5 x PhoA abundance). To the authors' knowledge, this is the first observed direct correlation between protein abundances and APase activity within Synechocystis.
An interesting observation in relative levels of protein abundances are the significant differences between abundances of proteins in the 3% P i and 0.3% Pi cultures. PhoA, and PstS12 are both significantly more abundant in the 0.3% P i than in 3% P i (Figure 2A), whereas there is no significant difference in abundance of Ppa proteins between the two cultures. This suggests the possibility of a two-tier strategy in cell acclimation: (i) a phased response, whereby protein abundance is putatively associated with/ proportional to internal or external phosphate concentrations, and (ii) a switched response, whereby the cell has a possible biochemical 'marker' for activation, for example an as yet undefined external phosphate concentration, and which below this abundance levels of that protein are constitutively maintained within the cell. However, more research is required to investigate this.
It has been previously demonstrated that the two periplasmic phosphate-binding proteins PstS12 have unique enzymatic and regulatory properties [22]. pstS1 encodes a low-affinity, high velocity P i transporter protein that was expressed to a significantly greater extent than the pstS2 transcript when cells were grown in P i -replete conditions. However, pstS2, a high-affinity, lowvelocity transporter, was expressed at significantly higher levels under P i -stress conditions [22]. In addition, the disruption of pstS1 caused constitutive expression of the pho regulon, indicating a role in external P i sensing [22]. The results here, in part, support those findings. However, our results also infer that elevated expression of pstS2 is not limited to a stress response, but is also an acclimation response. PstS2 is significantly higher than PstS1 within 3% and 0.3% P i cultures, and the abundance of PstS2 within the 0.3% P i culture is significantly higher than in the 3% P i culture ( Figure 2A).

Light harvesting and photosystems
Light harvesting within Synechocystis is accomplished through large multi-protein complexes, called phycobilisomes, consisting of phycobiliproteins (PBPs). Phycobilisomes are composed of a core complex surrounded by a tiered array of pigmented allophycocyanins, phycocyanins and non-pigmented linker peptides that harness and siphon the light energy to PSII [37]. These structures are significantly affected by prolonged exposure to low P i levels in the medium ( Figure 3A, Table 1). Within cyanobacteria, phycobilisome loss varies between species, and specifically under different nutrient deprived conditions. For example, a significant reduction of cyanobacterial phycobilisome content, known as chlorosis, is well known during nitrogen deprivation [38,39], and yet a recent proteomic study of Synechocystis during CO 2 limitation showed a minimal decrease in phycobiliprotein abundance [40]. However, that result is in contrast to previous transcriptome experiments [41,42]. Nevertheless, a study of Synechococcus levels of bleaching varied significantly between growth in nitrogen, sulphur and phosphorus deficient media, possibly reflecting differentially regulated subprocesses [43]. Interestingly, Wegener et al., [44] demonstrated that, after 6 days of P i depletion, phycobilisomes and pigment biosynthesis were unaffected, yet their cells demonstrated significant chlorosis. This is unexpected and in contrast to our results, in which significant reduction of phycobilisome structures corresponded with chlorosis. It is difficult to immediately explain this disparity; however, the difference in timescales between both experiments may hold a clue.
It is interesting to note the significantly linear relationship within the phycocyanin group and allophycocyanin The phosphate concentration in the samples was determined using the acid molybdate method [37], and p-nitrophenylphosphate as substrate. Only alkaline phosphatase activity was detected.
group of proteins. A statistical analysis of the phycobiliprotein abundances between the 3% and 0.3% P i cultures revealed that there is no significant difference between the phycocyanins (CpcA-G, Figure 3A) and the allophycocyanins (ApcA-E, Figure 3A) at the 3% P i level (p = 0.09, df = 32). However, there is a significant difference at the 0.3% P i level (p = 0.006, df = 32). This difference indicates that the light harvesting antennae of 0.3% P i culture cultures have significantly less of the phycocyanins in proportion to their allophycocyanin content than do the 3% P i culture cultures. This potentially suggests independent regulatory systems between the different PBP groups, or differential regulation of group specific proteases, whose activity is putatively dependent upon external P i concentrations. This is a reasonable hypothesis, as phycocyanins are attached externally to allophycocyanins through linker peptides, and light energy is funnelled from phycocyanins through allophycocyanins to PSII [37]. This regulation may be due to the organism attempting to reduce photosynthetically induced oxidative damage. Four proteins within photosystem II (PSII) and the photosynthetic electron transport chain (PETC) are differentially less abundant ( Figure 3B). Both PsbU and PsbW appear to be less abundant than in the control culture under both conditions, whereas PsbV is significantly less abundant only in the 0.3% P i culture. The extrinsic protein PsbV, alongside PsbU, is a critical protein in the oxygen evolving complex of cyanobacterial PSII complexes [45,46]. Indeed, PsbU appears to promote stability within the water-splitting PSII structure [47]. PsbW (characterized recently, and more commonly referred to as Psb28 within Synechocystis [48]) appears to be closely associated with PSII complexes, and more specifically to the biogenesis of the chlorophyll-binding CP47 protein [49]. As a consequence, it appears that when cells acclimate to low levels of ambient P i , light harvesting and structural integrity of the PSII assembly is compromised.
Ferridoxin NAPDH reductase (PetH, Figure 3B) is commonly associated with PSI and the terminal end of the PETC, nominally with regards to the production of reducing energy. However, in Synechocystis it has also been demonstrated to be closely associated with the phycobilisomes [50]. Within our study, the relative abundance of PetH is significantly less within the 0.3% P i culture, but not the 3% P i . This then, coupled with the PsbV observation, implies a strategic down regulation of PETC and PSII activity as ambient P i concentrations decrease. However, no other proteins associated with PSI were identified, and the suggestion that PSI function was decreased requires further validation in the future.
It is clear that ambient P i concentrations have a significant effect upon the photosynthetic machinery within Synechocystis. However, it is also clear that this did not mean a complete loss of function, as occurs during prolonged nitrogen deprivation [38], and represents a proportional loss of function, dependent upon P i concentrations. Our results present evidence of a response comparable to Synechococcus sp. PCC 7942 [43].

Central metabolism
The central metabolism of Synechocystis was affected by prolonged exposure and acclimation to reduced P i concentrations. Ten proteins were identified as being significantly differentially abundant in both 3% P i and 0.3% P i compared to the control cultures ( Figure 4A, Table 1). Three proteins that were more abundant than the control (in both% P i and 0.3% P i cultures) were transaldolase (Tal), 6-phosphogluconate dehydrogenase (decarboxylating) (Gnd) and glucose-6-phosphate 1dehydrogenase (Zwf ) ( Figure 4A). These proteins function within the 6 th , 3 rd and 1 st steps in the pentose phosphate pathway (PPP) respectively. Allied to this, 6-phosphogluconolactonase (Pgl), the 2 nd step in PPP, demonstrated a strong indication that it was more abundant in both the 3% and the 0.3% cultures ( Figure 4A), but this is not clear. This is an important observation, as the PPP acts to generate reducing energy (in the form of NADPH), and also generates metabolic precursors for nucleotide/nucleic acid and amino acid biosynthesis [51].
In contrast, three glycolysis and carbon fixation proteins, phosphoglycerate kinase (Pgk) and the two subunits of rubisco (RbcL and RbcS) were significantly less abundant in 3% P i and 0.3% P i vs the 100% P i controls ( Figure 4A, Table 1). These proteins are the central enzymes within the first two phases of the Calvin-Benson cycle (being the fixation of CO 2 , the reduction of 3-phosphoglycerate, and the regeneration of ribulose 1,5-bisphosphate). This cycle is critical in all photosynthetic organisms, and is fundamentally limiting to growth and reproduction. This result is unsurprising, given the significant reduction in photosynthetic light harvesting earlier observed in both 3% and 0.3% P i cultures. It is also interesting to note that the enzyme Transketolase (TktA), which functions in both the Calvin-Benson cycle and PPP was not differentially abundant. Interestingly, at the transcript level, gnd, tal and zwf were all strongly induced under nitrogen deprivation, as well as one of the two glycogen phosphorylases glpP (sll1367). The Calvin-Benson cycle genes rbcL and rbcS were also down regulated [52]. Our results demonstrate that the other glycogen phosphorylase (sll1356), rather than sll1367 is more abundant (see below), however the similarity in results is noteworthy. Osani and co-workers [52] concluded that nitrogen deprivation induces sugar catabolism, and that the PPP is the primary method of reducing power production. Our results confirm that P i deprivation also leads to a similar biochemical response, and thus indicate that the central metabolic response of the cell is similar for both N and P i deprivation.
However this response has a significantly different level of severity depending upon N or P i deprivation [43].
When considering energy metabolism (defined in this instance as the synthesis and degradation of the glycolytic/ PPP precursor glucose 6-phosphate), Figure 4B shows a significant difference between the relative abundance of two glycogen phosphorylation proteins (GlgP(1) & GlgP (2)). Both proteins are assumed to function to degrade glycogen, thereby generating D-glucose-1-phosphate in the preparatory, rate-limiting step before entry into glycolysis. However, the differential relative abundance between both proteins suggests differential functional roles within the cell. The enhancement of central PPP protein abundances highlighted earlier suggests that glycogen is being processed by GlgP (2) to support the production of NADPH and pentose sugars. As mentioned earlier, GlgP (1) rather than GlgP(2) was found to be differentially upregulated at the transcript level when subjected to N deprivation [52], which then suggests differing regulatory controls for each enzyme and condition. Also, Wegener and associates observed that sll1367 was more abundant than sll1356 under P deplete conditions [44], and so we must conclude that over short P starvation periods, sll1367 is preferred, and over longer, chronic, periods sll1356 predominates.

Transcription, translation, stress and hypothetical proteins
Six proteins out of 24 relating to transcription, translation and stress were significantly differentially abundant within both reduced P i cultures. An interesting group of proteins are the ATP-dependant Clp proteases, ClpC, ClpP1, ClpP2 and ClpB. These proteins are vital for growth and stress acclimation, and act to degrade denatured polypeptides and maintain cellular homeostasis [53]. Within Escherichia coli there is evidence that these proteins act in a multi-subunit complex, with the exclusion of ClpB (which acts independently) [54]. However, little is known about cyanobacterial Clp proteases, except that cyanobacterial ClpC is 90% similar to the ClpC in plant chloroplasts, is transcriptionally constitutively expressed at a level which appears to be unaffected by stress conditions, and that loss-of-function manipulation is generally fatal [55]. This last point emphasises the protein's role as an essential chaperone.
As such, it is interesting that the regulatory subunit, ClpC, was significantly lower in both reduced P i cultures, and yet one of the two identified isomeric forms of ClpP, ClpP1, demonstrated no significant differential abundance ( Figure 5). While this seems counterintuitive, later studies showed that ClpC does not interact with ClpP1 or ClpP2, but rather with ClpP3 and ClpP4. As such, two distinct and separate Clp protease complexes function within Synechococcus elongates PCC 7942 [56], which indicates that each complex functions to degrade differing substrates. At this time, the substrate for ClpC is unknown. Considering the other chaperone proteins identified, only GroL1 was differentially abundant ( Figure 5). This has been observed within Prochlorococcus marinus MED4 during high-light stress [57], but was not observed within MED4 during acclimation to low P i [18]. This abundance difference between species and environmental conditions is puzzling, and likely reflects other, unknown, contributory factors.
Translation appears to be affected as the elongation factor, EF-Tu (Tuf, Figure 5), which facilitates the entry of aminoacyl tRNA into the free site of the ribosome, was significantly lower in abundance within the 0.3% culture. EF-Tu is critical in successful translation, and acts as a powerful indicator that translation is lower within cells acclimated to long term P i deprivation. It is instructive to note that the other three elongation factors identified in our study (Gst, Tsf, and FusA) were unaffected, which may indicate a regulatory role for EF-Tu.
Two known stress response proteins were more abundant in low P i : rehydrin and SodB ( Figure 5). The functional role of rehydrin, a protein associated with desiccation stress in mosses [58], is unknown, and this represents the first recording of this protein being intrinsic to P i acclimation. In contrast, the function of the iron superoxide dismutase protein, SodB, is well characterised [59], and is primarily responsible for the cell's response to oxidative stress.
One biosynthetic protein was significantly differentially abundant within the P i -deplete cultures than the control, 3-oxoacyl-[acyl-carrier protein] reductase (FabG2, Figure 4B, Table 1), which participates in fatty acid biosynthesis. This is interesting as fatty acids play two main functions within the cell: (i) they are precursors of membrane lipids, and (ii) they accumulate for energy storage. However given their differential abundance, it would be expected that another critical protein required in this process, the acyl-carrier protein (acp) demonstrates no differential abundance in either the 3% P i , or the 0.3% P i culture. The reason for this is unclear, however the abundance of FabG2 is a strong indication that the cell over produced fatty acids when acclimating to low P i environments. Indeed, fatty acids have been speculated to have a role in stress tolerance within cyanobacteria, notably to desiccation, salt and temperature stress (see Singh et al. [60] for review). As well as energy storage, the production of lipids may help to stabilize nutrient acquisition machinery within the external membrane [60], and replace lipids damaged by reactive oxygen species, which have concurrent effects upon membrane fluidity and other cellular metabolic functions [61]. The role of fatty acids in desiccation stress is intriguing, specifically due to the increased abundance of the protein rehydrin within the 3% culture ( Figure 5, Table 1).
Twenty-one hypothetical proteins were identified within this study (Additional file 2: Table S1). Although at the time of writing, the functions of particular Figure 5 Relative abundances of proteins involved with transcription, translation, stress and uncharacterised hypothetical proteins. Non-significant observations are marked with a cross. Cultures grown in 3% P i are indicated with a square, whilst 0.3% cultures are indicated with a triangle. Empty datum points correspond to significant observations without a Bonferonni correction applied, whereas filled points are observations with the correction. The dotted line represents parity in abundance between control and experimental cultures. hypothetical proteins are unknown, it is an important observation that three proteins are differentially abundant within the cultures within this study. They are slr0645, slr1619 and slr2025 ( Figure 5, Table 1). Of the three, slr2025 was recently observed within a proteomewide survey of Synechocystis under CO 2 limitation. However, it was not considered differentially abundant [42], and so appears to be unimportant to acclimation to that environment. In our study, it was more abundant within the 3% P i culture.

Conclusions
Since Synechocystis typically inhabit rivers and lakes where the ambient P i concentrations range from nanomolar to micromolar ranges [62], our control cultures were acclimated to "luxury" P i concentrations, and hence the 3% and the 0.3% P i cultures, once re-acclimated, are more indicative of natural conditions. This study then emphasises the physiological mechanisms important for normal cellular reproduction and growth. The observed proteome acclimation response to environmental phosphate concentrations involved shifts in cellular abundances of P i acquisition and storage mechanisms, coinciding with changes in its photosynthetic machinery and a shift in central metabolism towards the production of reducing energy. While the coordination and control of this response was not uncovered, we and others have previously speculated that it is likely to be a complex interaction of internal regulatory systems initiated through the phoBR homologue of Synechocystisthe SphS-SphR two component system [10], and the activity of PstS1 [22].
We have shown that the observed abundance response of alkaline phosphatase is proportional to measured APase activity, and interestingly that there appears to be a coordinated and specific reduction of individual phycobiliprotein groups during acclimation. As has been previously reported for higher plants, these results provide some evidence that intracellular P i concentrations control photosynthetic activity in Synechocystis through the activation or deactivation of RuBisCO at different concentrations [63]. The similarity of the Synechocystis response to P i deprivation appears to be remarkably similar to prolonged nitrogen deprivation, although the magnitude of the response is greater in low nitrogen than in low P i . In both cases, the photosynthetic machinery was reduced significantly, and central metabolic processes shift to produce not just reducing energy but nucleotide sugars. We hypothesise that this cellular shift is designed to function in two ways: 1) that an increase in reducing energy provides the 'power' for the cell to stabilize and maintain the cell membranes, and 2) nucleotide sugars can be readily used as precursors for both ATP and GTP, as well as enabling the cell to quickly respond to changes in the environment through rapid production of RNA. The cell is therefore able to respond, grow and replicate rapidly.

Growth conditions
Synechocystis was principally grown in BG-11 medium [64] in 1 L conical flasks with a 0.5-L working volume shaken at 100 rpm. The P i replete BG-11 medium contained 40 mg/L of K 2 HPO 4 . For phosphate depletion experiments, the concentration of K 2 HPO 4 within BG-11 was prepared as 3% w/v (1.2 mg/L) and 0.3% w/v of the control P i replete BG-11 medium. The experimental design utilised biological duplicates of Synechocystis PCC 6803 cultured in each condition: (A) 100% P i (control), (B) 3% P i , and (C) 0.3% P i . Inocula for each culture were prepared by initial centrifugation of stock cultures followed by washing cells twice with sterilized deionised water and once with the respective P i reduced medium, prior to resuspension into the respective medium and experimental inception. Cultures were incubated in a Sanyo MLR-350H environmental chamber at 25°C on a 12-h light-dark cycle for 60 days with an initial optical density of 0.2. Irradiance was provided by cool-white fluorescent lamps at an incident intensity of 70 μE m -2 s -1 as measured by a three-dimensional QSL-2100 Light Sensor (Biospherical Instrument Inc, San Diego, CA). The growth rate was monitored and recorded using an Ultraspec 2100-Pro spectrophotometer (Biochrom, Cambridge, UK) at an OD of 730 nm.

Protein extraction and quantitation
Cells were harvested at day 60 by centrifugation at 5,000 × g for 5 min at 4°C. The cell pellets were resuspended in 500 mM triethylammonium bicarbonate buffer (TEAB) at pH 8.5 and proteins were extracted through mechanical cracking with liquid nitrogen [65]. Soluble proteins were recovered from the supernatant by centrifugation at 21,000 × g for 30 min at 4°C. The total soluble protein concentrate was then measured using the RC DC Protein Quantification Assay (Bio-Rad, Hertfordshire, UK) according to the manufacturer's protocol.

Acid/alkaline phosphatase assays
A subsample of cells broken by mechanical grinding with liquid nitrogen as described above was subsequently re-suspended in Tris-HCl buffer (pH 8.0) containing 5 mM MgCl 2 . Alkaline phosphatase assays were performed in duplicate as described by O'Loughlin et al. [66] at 30°C. The assay solution contained 50 mM Tris-HCl (pH 8.0), 20 mM MgCl 2 , and 5 mM pnitrophenyl phosphate with 0.01-0.1 mg cell-extract protein in a final reaction volume of 1 mL. For acid phosphatase assays, the Tris-HCl buffer was replaced with 50 mM succinate-NaOH buffer (pH 5.0).
Due to the presence of large quantities of chlorophylls in the cell-extract, detection of p-nitrophenol production by means of the widely used absorbance measurement at 412 nm was not possible. Reactions were therefore quenched with 0.2 vol of 3 M trichloroacetic acid solution following addition of cell extract protein and a duplicate reaction tube quenched 10 min later. The resultant reaction supernatants were cooled on ice for 10 min prior to centrifugation at 20,000 × g for 5 min to remove precipitated protein, following which the phosphate concentration in the samples was determined using the acid molybdate method of Fiske and SubbaRow [67]. 'No substrate' and 'no cell-extract' controls were included and activity was expressed as nmol of P i released per min per mg of cell-extract protein, taking the control reactions into account.

SCX prefractionation and iTRAQ
Approximately 100 μg of protein from each sample was placed in PCR clean LoBind microcentrifuge tubes (Eppendorf, Cambridgeshire, UK), then reduced, alkylated and digested as previously reported [18]. The resultant peptide digests were then labelled using 6 labels from an 8-plex iTRAQ chemical reagents kit (AB Sciex UK Limited, UK), with phosphate replete control samples (nominated as 100% P i ) tagged with the 113 and 114 labels, cells grown in 3% P i tagged with 115 and 116, and the 0.3% phosphate-grown cells tagged with the 117 and 118 labels. Primary peptide fractionation was carried out through strong cation exchange (SCX) on a BioLC HPLC unit (Dionex, Surrey, UK) with a Poly SULFOETHYL A ™ column (PolyLC, Columbia, MD, USA). The column used 5 μm particle size, and had dimensions of 200 mm length with an internal diameter of 2.1 mm and a 200 Å pore size. The buffers used were Buffer A (10 mM KH 2 PO 4 with 20% HPLC grade acetonitrile (ACN) at pH 2.5) and Buffer B (10 mM KH 2 PO 4 with 20% HPLC grade acetonitrile (ACN) and 500 mM KCl at pH3) with a gradient of 0% B for 5 min, 0-40% B for 30 min, 40-100% B for 10 min, 100% B for 5 min, and 0% B for 5 min. Before fractionation, the digests were dried in a vacuum centrifuge and resuspended in 200 μL Buffer A. In order to remove salts and unbound iTRAQ reagents, samples were injected onto the column, and manual acquisition was initiated. This allowed Buffer A to flow through the column, leaving bound peptides attached and purging all non-bound material. Two injections were completed before initiation of the gradient. The flow rate was maintained at 200 μL min -1 . A UV detector (UVD170U) was used to monitor the fractionation process, and the entire operation was controlled and through Chromeleon software (Dionex/LC packings, the Netherlands). Fractions were collected each minute for the duration of the run with a Foxy Jr. Fraction Collector (Dionex). Fractions were selected for subsequent MS/MS analysis according to SCX chromatogram intensity.
Mass spectrometric analysis was performed on a QStar XL Hybrid ESI Quadrupole time-of-flight tandem mass spectrometer, ESI-qQ-TOF MS/MS (Applied Biosystems, Framingham, MA; MDS-Sciex, Concord, Ontario, Canada), coupled with an Ultimate 3000 online capillary liquid chromatography (LC) system (Applied Biosystems, Framingham, MA), with a PepMap C-18 RP column (LC Packings) set to a constant flow rate of 0.3 μL min -1 . Selected fractions were dried and resuspended in 10 μL of Buffer A prior to analysis. To prevent salts, and other contaminants entering the mass spectrometer, a C-18 column clean up (The Nest Group, Inc. Southborough, MA) of each fraction was performed. Cleaned samples were then injected into the online nanoflow LC-MS/MS unit where the buffers were Buffer A (3% (v/v) ACN with 0.1% (v/v) formic acid (FA)), and Buffer B (97% (v/v) ACN with 0.1% (v/v) FA). The gradient applied for the second dimension of chromatography was 3% Buffer B for 3 min, 3 -40% Buffer B for 70 min, 90% Buffer B for 5 min, and 3% Buffer B for 7 min. The data acquisition protocol in the mass spectrometer was set to positive ion mode, and the addition of formic acid to the buffers was used in order to promote protonation. Peptides were selected by the mass spectrometer for further tandem MS/MS due to observed charge states of +2 and +3.

Data analysis
Mass spectrometry data analysis, peak list conversion, peptide identification and quantitation was carried out using the combination of Analyst QS ver. 1.1 (ABSciex, Foster City, CA) and Phenyx 2.6 (Geneva Bioinformatics, Geneva, Switzerland) software against the UniProt Synechocystis (accessed May 2010). The databases used for searching were Synechocystis PCC6803 (including plasmids), and the NCBI non-redundant database (www. ncbi.nlm.nih.gov/, Accessed 01/07/10). Searches of the Synechocystis database were conducted using a targetdecoy approach (reversed sequence decoy). All searches were performed with the parameter settings: 0.1 Da MS scan tolerance, 0.15 Da MS/MS scan tolerance, strict trypsin cleavage with one allowable missed cleavage and a minimum of 20% of combined y, y 2+ , b, b 2+ ions. Acceptance threshold for peptide identification were set to p-value ≤ 1 × 10 -4 with a peptide score ≥ 5. Protein identification was then set to include only matches with at least a score of 7 (AC score ≥ 7).
Statistical inference was obtained using a t-test comparison between the reporter ions' intensities, as previously detailed in Mukherjee et al. [68] and Pham et al.