Hepatocyte growth factor (HGF) is a pleiotropic cytokine which can lead to cancer cell proliferation, migration and metastasis. In multiple myeloma (MM) patients it is an abundant component of the bone marrow. HGF levels are elevated in 50% of patients and associated with poor prognosis. Here we aim to investigate its source in myeloma.HGF gene expression profiling in CD138+ cells isolated from bone marrow aspirates of healthy individuals and MM patients was performed by microarray analysis. HGF protein concentrations present in peripheral blood of MM patients were measured by enzyme-linked immunosorbent assay (ELISA). Cytogenetic status of CD138+ cells was determined by fluorescence in situ hybridization (FISH) and DNA sequencing of the HGF gene promoter. HGF secretion in co-cultures of human myeloma cell lines and bone marrow stromal cells was measured by ELISA.HGF mRNA levels in bone marrow core biopsies from healthy individuals and myeloma patients were quantified by real-time PCR. + cells showed elevated HGF mRNA levels in myeloma patients. HGF mRNA levels in biopsies and in myeloma cells correlated. Quantification of HGF protein levels in serum also correlated with HGF mRNA levels in CD138+ cells from corresponding patients. Cytogenetic analysis showed myeloma cell clones with HGF copy numbers between 1 and 3 copies. There was no correlation between HGF copy number and HGF mRNA levels. Co-cultivation of the human myeloma cell lines ANBL-6 and JJN3 with bone marrow stromal cells or the HS-5 cell line resulted in a significant increase in secreted HGF.HGF gene expression profiling in both bone marrow core biopsies and CD138We here show that in myeloma patients HGF is primarily produced by malignant plasma cells, and that HGF production by these cells might be supported by the bone marrow microenvironment. Considering the fact that elevated HGF serum and plasma levels predict poor prognosis, these findings are of particular importance for patients harbouring a myeloma clone which produces large amounts of HGF. Multiple Myeloma (MM) is a neoplasm of terminally differentiated antibody-producing B-cells . MalignaHepatocyte growth factor (HGF) is a pleiotropic cytokine capable of inducing mitogenesis and morphogenesis in target cells by activation of its transmembrane receptor tyrosine kinase c-MET. In myeloma, HGF-c-MET signaling was reported to induce myeloma cell proliferation and survival ,5. We anUnder normal conditions, HGF and c-MET are primarily expressed by mesenchymal and epithelial cells, respectively, representing an important signaling pathway for mesenchymal-epithelial interaction. However, hematopoietic cells such as B-cells are also capable of expressing both HGF and c-MET, but the expression is depending on stage of cell maturation, and results in either c-MET or HGF expression ,12. We hHGF overexpression in malignant PCs or due to a reactive process within the bone marrow which is a result of the presence of malignant PCs. Since the origin of excess HGF in myeloma patients is still unknown, we hypothesized that the bulk of HGF found in myeloma patients is produced by malignant PCs, and not by the bone marrow microenvironment. We therefore performed experiments which were aimed at identifying the source of excess HGF. In summary, we show by microarray, real-time PCR, fluorescence in situ hybridization, Sanger DNA sequencing and co-cultivation experiments that in patients with very high serum levels of HGF protein, malignant PCs and not the bone marrow microenvironment are responsible for excess HGF production. Furthermore, serum HGF reflects overexpression of HGF in the malignant PCs.High HGF levels found in the blood and bone marrow of myeloma patients could either be the result of Samples used in this study comprised blood sera from multiple myeloma patients, bone marrow aspirates taken from healthy individuals and from patients suffering from different stages of disease as defined based on the International Myeloma Working Group consensus guidelines and bone marrow core biopsies isolated from healthy individuals and MM patients . Human m+ magnetic-activated cell sorting (MACS) Microbeads  essentially as described elsewhere [Serum samples were taken at diagnosis and before the initiation of treatment. Bone marrow aspirates and bone marrow core biopsies were taken from the left or right posterior superior iliac crest at diagnosis before treatment was initiated using established surgical procedures at the University of Arkansas Medical Sciences, Little Rock, Arkansas, USA or at the Department of Hematology/Regional Research Biobank of Central Norway, St. Olavs University Hospital, Trondheim, Norway. Plasma cells were purified from bone marrow aspirates by CD138lsewhere . The bonSamples were collected after informed consent was given by the patients. An institutional review board-approved consent form, which was in accordance with the Declaration of Helsinki, was used to receive patient consent. The study was approved by the Norwegian Regional Ethics Committee (REK 2011–2029), and by the Institutional Review Board of the University of Arkansas for Medical Sciences.6 cells) using the AllPrep DNA/RNA Mini Kit . The RNeasy Fibrous Tissue Kit (Qiagen) was used to extract total RNA from ultra-low temperature (liquid nitrogen) preserved bone marrow core biopsies.Genomic DNA and/or total RNA was isolated from normal PCs, primary myeloma PCs and myeloma cell lines , 14 patients diagnosed with monoclonal gammopathy of undetermined significance (MGUS), 34 patients with smouldering MM (SMM), 344 MM patients and 45 HMCLs were retrieved from the NIH Gene Expression Omnibus17, which can be found under accession number GSE2658. The Mann–Whitney test (two-tailed) was performed for analysis of statistical significance.Gene expression profiling was performed as previously described using the Affymetrix U133Plus2.0 microarray  -22. Micr+ cells purified from bone marrow aspirates of 24 MM patients were quantified by TaqMan® real-time PCR. Total RNA (1.0 μg) was reverse-transcribed using the High Capacity RNA-to-CDNA Kit , applying oligo(dT) primers. The HGF (Hs00379140_m1) TaqMan® probe was used to detect gene expression and GAPDH (Hs99999905_m1) was used as endogenous reference .HGF mRNA levels in bone marrow core biopsies taken from 19 healthy individuals and 46 MM patients and in CD138HGF promoter fragments present in CD138+ cells purified from bone marrow aspirates from 12 MM patients were amplified from genomic DNA templates using the PfuUltra II Fusion HS DNA Polymerase . To facilitate amplification, the HGF promoter was divided in four overlapping segments. For primers see Additional file HGF promoter of CD138+ cells purified from bone marrow aspirates of 24 MM patients were amplified as described elsewhere [The deoxyadenosine tract elements (DATE) present in the lsewhere  and sub-+ cells purified from bone marrow aspirates of 24 MM patients. Probes for FISH were made from Bacterial Artificial Chromosome (BAC) clones . BAC clones RP11-117 L18 and RP11-433O12 which are centromeric to HGF were labeled in SpectrumOrange and BAC clones RP11-657 J19 and RP11-451D20 which are telomeric to HGF were labeled in SpectrumAqua. Centromeric enumeration probe 7 in green  was used to assess the chromosome copy number. Sample preparation and microscopy was performed as earlier described [FISH was performed on CD138escribed .et al.[− bone marrow mononuclear cells were seeded in cell culture flasks, and after 3 days non-adherent cells were removed. The remaining cells were expanded for three to four weeks. Stromal cells from ten different patients were mixed to obtain a batch of standardized BMSC. Each batch of BMSC was characterized by immunophenotyping, using an LSRII flow cytometer . The bone marrow stromal cells consisted essentially of fibroblast-like cells [Preparation of BMSC was performed as described in detail by Misund et al.. In shorke cells .4 cells per well (0.5 mL) into 24 well plastic plates and allowed to adhere for 24 h at 37°C in a humidified atmosphere containing 5% CO2. Then, 2 to 6 × 104 myeloma cells  were added and cultivation continued until supernatants were harvested after 48 h. Later, the levels of HGF in the supernatants were measured by ELISA. The cell lines HS-5 [For co-cultivation experiments, BMSC or HS-5 cells , were senes HS-5 , U266 [2nes HS-5 , and thenes HS-5  were purnes HS-5  and INA-nes HS-5  were kinnes HS-5  was a kines HS-5  and OH-2nes HS-5  cell lin4 BMSC per well (0.5 mL) were seeded into inserts of 24 transwell plastic plates (pore size of 0.4 μm) and allowed to adhere for 24 h at 37°C in a humidified atmosphere containing 5% CO2. Then, 6 × 104 ANBL-6 cells or 2 × 104 JJN3 cells per well (0.1 mL) were added to the lower chambers. Supernatants were harvested after 48 h, and the HGF levels were measured by ELISA.For the cultivation of BMSC with myeloma cells in transwells, 3 × 10HGF protein concentrations were quantified in a total of 53 blood sera taken from MM patients or cell supernatants using the DuoSet ELISA Development kit . Assay was performed according to manufacturer’s instructions.Results were considered statistically significant when p values were less than 0.05. Skewed variables were logarithmically transformed before entering a parametric analysis. Comparisons between groups were performed by the Mann–Whitney U test. To investigate linear correlations linear regression analysis was used.We have earlier shown that about 50% of myeloma patients have elevated HGF protein levels in the blood serum and in the bone marrow as compared to healthy individuals. However, the measured values showed considerable variation within each group ,9,10. El2 = 0.106). This suggests that the HGF mRNA content in bone marrow core biopsies from a group of MM patients is not associated with the proportion of myeloma cells in the bone marrow of the same patients.Next, the possibility that elevated HGF mRNA levels could be related to the percentage of malignant PCs present in the bone marrow was examined Figure B. Linear+ cells isolated from bone marrow aspirates of healthy individuals  and patients diagnosed with monoclonal gammopathy of undetermined significance , smouldering MM , and MM . Human myeloma cell lines were also included   to the HGF mRNA levels measured in CD138+ cells (n = 46) isolated from bone marrow aspirates taken at the same site showed significant correlation (R2 = 0.633) as shown in Figure HGF gene expression profiles (GEP) of CD138+ cells (n = 29) to HGF protein concentrations in peripheral blood serum (n = 29) measured in corresponding samples  indicating association between HGF mRNA produced by CD138+ cells and HGF serum concentrations. In summary these data indicate that the myeloma cells are the primary source of HGF in the bone marrow of myeloma patients with elevated levels of HGF.As CD138elation R = 0.633 elation R = 0.633 i.e. approximately 30%, shows highly elevated HGF serum concentrations. The latter group has a particularly poor prognosis [HGF-expressing myeloma cells to define this subgroup and raises the question of what the underlying mechanism is which leads to this phenotype.HGF serum values are frequently (approx. 50%) elevated in myeloma patients and a subgroup of myeloma patients, rognosis , which pHGF amplifications or translocations could explain the variation in HGF mRNA in malignant plasma cells, we analyzed the number of HGF gene copies by FISH (n = 24) and quantified HGF mRNA levels in the same samples by real-time PCR (n = 24). We found that the plasma cells from these patients contained one, two or three copies of HGF. As summarized in Table HGF copy number and HGF mRNA levels in these cells. Moreover, we found no evidence of translocations involving HGF. Thus, the high HGF mRNA expression in these malignant PC clones is not due to amplifications or translocations of HGF. Details of gene copy numbers can be found in Additional file To see if HGF could explain the differences in HGF mRNA expression, 12 patient samples which were analysed by FISH were further investigated by sequencing of the proximal HGF promoter. From the 24 samples analysed by FISH were the 5 samples that showed the lowest HGF serum concentrations  and the 7 samples that showed the highest HGF serum concentrations  chosen. The HGF 5’-UTR of the twelve samples were analyzed by at least three independent overlapping sequencing reactions, considering only high quality sequence traces. The region from approximately −3000 bp to +120 bp relative to the transcription start site  between the length of DATE and HGF mRNA levels in corresponding samples  with various myeloma cell lines for 48 hours, before measuring the produced HGF present in the co-culture supernatant by ELISA.Co-cultivation of ANBL-6 or JJN3 cells with BMSC led to a significant increase in HGF production Figure A in the We also co-cultured ANBL-6 or JJN3 cells with the HS-5 cell line Figure B. Also iTo see if cell-cell contact is necessary to obtain this effect, we performed the same experiments, but separated the stromal cells from the myeloma cell lines by transwells. As shown in Figure et al. showed that HGF induces proliferation and cell survival in the majority of HMCLs investigated and in about 50% of malignant PCs isolated from myeloma patients [+ cells inhibition of the HGF – c-MET signaling pathway induces cell death and counter acts the proliferative potential induced by HGF [HGF is overexpressed in the bone marrow of myeloma patients. This is in agreement with the findings made by Mahtouk et al. who showed by performing a microarray study that HGF is expressed in both malignant PCs and in cells of the BM microenvironment, but not in healthy PCs [i.e. in approximately 50% of patients [HGF gene expression profiling data reflect these findings as the observed HGF mRNA levels measured in CD138+ cells isolated from bone marrow aspirates of healthy individuals and myeloma patients at different disease stages varied widely within each sample group. Interestingly, despite the large sample range, HGF mRNA levels in malignant PCs were significantly elevated if compared to HGF mRNA in CD138+ cells isolated from healthy individuals. This is corroborated by a microarray study performed by Zhan et al., were they found HGF to be the only cytokine that was upregulated in myeloma cells as compared to PCs of healthy individuals [+ cells as the main source of excess HGF in myeloma patients. An investigation of whether HGF protein levels in patient sera and HGF protein levels in corresponding CD138+ cell samples correlate or not would further strengthen these findings, however such experiments could not be performed as CD138+ cells are available only in limited numbers and become apoptotic when cultured for an extended time period.In myeloma the importance of HGF – c-MET signaling is still unclear although Derksen patients ,5. In a d by HGF . These flthy PCs . HGF valpatients ,7. Also patients -14. Our ividuals ,20. InveHGF promoter region of CD138+ cells isolated from twelve patients. No point mutations could be detected. Despite the large number of SNPs described for the sequenced region, only three SNPs were present, i.e. Rs3735520, Rs11763015 and Rs149178895. SNP Rs149178895 is located at position 2309 based on the HGF reference sequence (NG_016274.1), was found only once in patient MM 14, and two patients were homozygous for a dC to dT transitional mutation at position −1652 (Rs3735520) relative to the transcription start site. SNP Rs3735520 was found to associate with end-stage lung disease in Japanese systemic sclerosis patients, and carriers of the HGF promoter with the HGF −1652 TT allele had a relative inability to increase circulating HGF levels. By functional studies, the HGF promoter carrying the HGF −1652 TT allele was reported to have lower transcriptional activity than the promoter carrying the CT or CC allele, possibly due to the binding of a negative transcriptional regulator [Investigating the molecular mechanisms behind the HGF production in myeloma cells, we looked for genetic aberrations possibly responsible for the excess HGF production. However, we found no apparent mutations or amplifications of the HGF gene that could explain elevated HGF production. To clarify if a mutation could be responsible for excess HGF, we sequenced the In breast cancer, a negative regulatory deoxyadenosine tract element (DATE) composed of about 30 adenosines was described to be present in the HGF promoter. This element was described to be important for gene silencing in breast tissue. If DATE becomes shortened by at least five adenosines, the element loses its repressive effect resulting in HGF expression in breast tissue and breast cancer cells . We alsoHGF expressing phenotype of certain myeloma cell clones points to other mechanisms that induce excessive HGF production. We therefore investigated if the bone marrow microenvironment could induce excessive HGF production in certain myeloma cells. By performing co-cultivation experiments of BMSC with various myeloma cell lines we found that co-cultures of stromal cells with ANBL-6 cells or JJN3 cells led to a marked increase in HGF production. The co-cultivation of BMSC with U266 cells led as well to an increased HGF production, although this effect was not significant.The absence of mutations that could explain the high HGF overexpression in malignant PCs.The increase in HGF production in co-cultures of myeloma cells with stromal cells could also be seen with different types of stromal cells. The BMSC applied here are mainly fibroblast-like cells obtained from the CD138 negative fraction of bone marrow mononuclear cells isolated from myeloma patients. The HS-5 cells are a fibroblastic cell line immortalized with papilloma virus genes E6 and E7. These cells were found to support proliferation of hematopoietic progenitor cells without the need for exogenous factors . CultivaInterestingly, we observed increased HGF production in co-cultures of BMSC with the cell lines ANBL-6 and JJN3, but not with other myeloma cell lines. Both ANBL-6 and JJN3 cells produce substantial amounts of HGF also when cultured alone. This indicates that stromal cells are only able to induce elevated HGF production in myeloma cells which already are capable of making HGF.+ cells. Furthermore, we demonstrated that neither cytogenetic aberrations of the HGF gene, nor mutations in the HGF promoter, but rather exogenous factors present in the bone marrow microenvironment lead to increased HGF production by malignant PCs. The data showing that BMSCs increase HGF production in myeloma cells is consistent with the view that myeloma cells largely rely on and respond to the bone marrow niche. These findings might help to identify a subpopulation of myeloma patients which suffer from a myeloma cell clone that produces large amounts of HGF. This could be of value in clinical applications, and in particular in relation to the bone disease of multiple myeloma, where elevated HGF levels associate with severity of disease.In this study, we investigated the origin of elevated HGF levels found in myeloma patients. The main result presented here is that in multiple myeloma malignant plasma cells are the prime source for the high HGF levels in the bone marrow and peripheral blood serum. As shown in previous studies, HGF protein levels in plasma and serum from myeloma patients show large variations and we here confirm this on the mRNA level measured in CD138in situ hybridization; HGF: Hepatocyte growth factor; HMCL: Human myeloma cell line; MGUS: Monoclonal gammopathy of undetermined significance; MM: Multiple myeloma; NPC: Non-myeloma plasma cell; PC: Plasma cell; R.Q.: Relative quantity; SMM: Smouldering multiple myeloma.BMSC: Bone marrow stromal cells; DATE: Deoxyadenosine tract element; ELISA: Enzyme-linked immunosorbent assay; FISH: Fluorescence The authors declare that they have no competing interests.CR, ET, TKV and GB performed experiments. CR and ET designed the research and analyzed the data. AW provided samples and reviewed the work. TSS gave suggestions, proofread and reviewed the manuscript. MB and AS supervised the research and provided funding. All authors have read and approved the final manuscript.Table S2. Cytogenetic status of the patient samples investigated by fluorescence in situ hybridization. Primers for the amplification of the HGF promoter, DATE nested PCR primers and sequencing primers. Click here for file


Halobacterium salinarum via a direct interaction with a cis-regulatory sequence in their promoters. This interaction is abolished in the presence of glucose. Although much is known about the effects of TrmB at the transcriptional level, it remains unclear whether and to what extent changes in mRNA levels directly affect metabolite levels. In order to address this question, here we performed a high-resolution metabolite profiling time course during a change in nutrients using a combination of targeted and untargeted methods in wild-type and ΔtrmB strain backgrounds. We found that TrmB-mediated transcriptional changes resulted in widespread and significant changes to metabolite levels across the metabolic network. Additionally, the pattern of growth complementation using various purines suggests that the mis-regulation of gluconeogenesis in the ΔtrmB mutant strain in the absence of glucose results in low phosphoribosylpyrophosphate (PRPP) levels. We confirmed these low PRPP levels using a quantitative mass spectrometric technique and found that they are associated with a metabolic block in de novo purine synthesis, which is partially responsible for the growth defect of the ΔtrmB mutant strain in the absence of glucose. In conclusion, we show how transcriptional regulation of metabolism affects metabolite levels and ultimately, phenotypes.Previous work demonstrated that the TrmB transcription factor is responsible for regulating the expression of many enzyme-coding genes in the hypersaline-adapted archaeon  H. salinarum, an enzyme functioning at a central branch point in metabolism, exhibits only limited allosteric regulation [The regulation of metabolism is a key challenge faced by all organisms. In unpredictable and fluctuating environments, cells must produce the same metabolic outputs to thrive. Although many central metabolic processes are well conserved across many species  and havegulation . DespitePyrococcus furiosus demonstrated that TrmB binds DNA in the absence of its inducing sugar. Depending on the position of the TrmB cis-regulatory sequence relative to the transcription start site, TrmB can both activate and repress transcription [Thermococcus kodakarensis, was shown to function as a global transcriptional regulator of gluconeogenic and glycolytic pathways [Halobacterium salinarum, TrmB functions as a central regulator of carbon metabolism. TrmB directly regulates over 100 genes in the absence of glucose [trmB (ΔtrmB) has been generated [ΔtrmB mutant strain exhibits wild-type growth rate and physiology when glucose is added to the medium [Previous work identified the TrmB family of transcriptional regulators as regulators of carbon metabolism. Biochemical assays in the hyperthermophilic archaeon cription . A TrmB pathways . In the  glucose  and indi glucose , which r glucose . The add glucose ,10. The enerated . This ste medium .H. salinarum cannot metabolize glucose for energy. No active transport of glucose [H. salinarum cannot convert 13C labeled glucose to 13C labeled pyruvate [Intriguingly, previous work suggests that  glucose  has been glucose ,13 has b glucose ; and H. pyruvate . Additiopyruvate .ΔtrmB mutant strain under gluconeogenic conditions. Because TrmB regulates a large and diverse regulon, understanding how mis-regulation of these genes affects metabolism can reveal novel enzymes and hitherto unrecognized connections between metabolic pathways. For these reasons, here we conducted metabolomics profiling experiments in the ΔtrmB mutant strain and the Δura3 isogenic parent strain over a time course of 10 hours, which included a glucose stimulus. By interpreting the time course metabolite data in the context of previously collected dynamic gene expression and TrmB-DNA binding measurements [ΔtrmB mutant strain in the absence of glucose leads to a defect in phosphoribosylpyrophosphate (PRPP) production, which causes a metabolic block in purine biosynthesis. We present evidence suggesting that this metabolic block is responsible for the up-regulation of genes encoding enzymes involved in purine synthesis in the ΔtrmB mutant strain in the absence of glucose. This block in purine synthesis is partially responsible for the growth defect of the ΔtrmB mutant strain in the absence of glucose. Taken together, these results further both a general understanding of the effects of transcriptional regulation on metabolite level and a deeper understanding of the regulation of specific pathways.Although the gene expression changes caused by TrmB and their evolutionary rationale have been explored ,9,15, itH. salinarum and other archaea [trmB (ΔtrmB) and its isogenic parent strain (Δura3). For collection of both targeted and untargeted data types, the ΔtrmB mutant and Δura3 isogenic parent strains were grown on amino acids as the source of carbon and energy to mid-logarithmic phase (OD600 ~ 0.2–0.5) in defined medium, then sampled two or three times before and seven times after the addition of glucose . Because our untargeted protocol has not been previously validated in halophilic archaea, and because the extraction solvent chosen for an assay can bias metabolite recovery [R2 > 0.55, p < 10−16), suggesting good reproducibility between different cultures, extraction solvents, and detection methods. Based on the regression fit of the untargeted GC-MS to the targeted data . Metted data , previouted data . Taken ttrations , and valΔtrmB knockout mutant and the Δura3 isogenic parent strain, many showed distinct patterns between strains (p < 0.005) and cluster 4, which is significantly enriched in peptides (p < 0.01) exhibited the most significant differences between the ΔtrmB knockout mutant and the Δura3 isogenic parent strain in the absence of glucose but not in its presence . This is because the filter-based sample collection method used to harvest the samples for untargeted dynamic analysis resulted in ~3 fold more dilute samples than the centrifugation-based method used to collect the samples for the previous study [trmB mutant. Together, these data suggest that TrmB, a transcription factor regulating metabolic enzyme-coding genes [A total of 125 metabolites were detected in the untargeted samples. Of these, 91 were positively ascribed to known compounds and classified into 8 pathways . The tem strains , S2 Fig.presence , suggest glucose , S1 Fig.ic phase . The preic phase  between us study , resultiH. salinarum before and after the addition of glucose, we sampled the optical density of the cultures of the ΔtrmB mutant strain and the Δura3 isogenic parent strain every 10 minutes before, during, and after the addition of glucose during mid-log growth in CDM . We calculated the instantaneous growth rate during each of these 10 minute periods in order to determine how growth rate changes after the addition of glucose. The addition of glucose to the Δura3 isogenic parent did not appear to cause a significant change in growth rate , suggesting that a defect in purine metabolism may contribute to the growth defect of the ΔtrmB knockout mutant strain.In order to determine which metabolites may be linked to changes in growth rate, we calculated the correlation between the level of each metabolite at each time point in each strain and the instantaneous growth rate at those time points in those strains. Seven of the 125 metabolites were significantly anticorrelated with growth rate, including three gamma-glutamyl amino acids as well as unidentified metabolites . Based oyl cycle . Althougalinarum , functiovolcanii . These o glucose , althougde novo purine synthesis [ΔtrmB mutant in the absence of glucose . Previous work has shown that purines are readily taken up by H. salinarum and integrated into biomass and nucleic acids [ΔtrmB strain in the absence of glucose  is expressed at the same level in both strains regardless of glucose level  proceeding from glucose-6-phosphate, to 6-phosphogluconate, ribulose-5-phosphate, ribose-5-phosphate and ultimately to PRPP . In ordeic data , Fig 7)..ΔtrmB muogenesis ,9 requir glucose .H. salinarum. In order to understand how transcriptional regulation of enzyme coding genes affects metabolism, we performed targeted and untargeted measurements of the metabolome of H. salinarum during a change in nutrient conditions. We found that the transcriptional regulation causes substantial changes in intracellular metabolite levels, which cause changes in physiology. Specifically, we identified a metabolic block in de novo purine synthesis in the ΔtrmB mutant strain in the absence of glucose, which is partially responsible for the observed growth rate defect. Combining dynamic metabolite and gene expression data, we showed that this block was due to a defect in PRPP caused by mis-regulation of genes encoding enzymes involved in gluconeogenesis and therefore a lack of OPPP substrates. Taken together, these data suggest that transcriptional regulation of enzyme coding genes is an important mechanism for regulating metabolism.Understanding the regulation of metabolism in archaea remains a central challenge to successfully tapping the vast reservoir of pathways and compounds in these organisms for industrial applications. Previous studies have identified TrmB as a central transcriptional regulator of metabolism in Halobacterium salinarum NRC-1 (ATCC strain 700922) was used as the wild-type strain background. Experiments were performed in two previously constructed strains, one containing an in-frame deletion of VNG1451C  and itsB, [ura3 .-1 uracil to complement the ura3 deletion. Cultures were routinely grown at 42°C while shaking at 225 r.p.m. under low ambient light.Cells were grown routinely in Complete Defined Medium (CDM) containing 19 amino acids [ΔtrmB mutant strain and its isogenic parent strain Δura3 were grown at 42°C under continuous shaking (~225 r.p.m.) in a Bioscreen C automated growth curve analysis system  to mid-logarithmic phase. Glucose, sucrose control, or nothing was added to the wells once mid-logarithmic phase was reached. Optical density at 600 nm was measured every 10 minutes for each sample during the duration of the experiment. Instantaneous growth rate was calculated from the log transformed and LOWESS-smoothed data using the bsd Analysis Function previously described [In order to assess instantaneous growth rate during glucose addition, 200 μl cultures of the escribed . In ordeΔtrmB mutant strain and its isogenic parent strain Δura3 in CDM supplemented with 100 μM concentration of the purines indicated in To measure the growth of the Δura3 and ΔtrmB strains at time points as indicated in H. salinarum lyses readily in methanol and other solvents because of its requirement for high salinity, cells were lysed on the membrane filter using 1 ml of ice-cold 80% methanol with extraction standards, ice-cold 100% methanol with extraction standards, or 1 ml 50% acetonitrile with 0.3% Formic acid as indicated (Cells were grown to mid-logarithmic phase (OD ~ 0.3) in CDM as described above. For metabolomics time courses, 10 ml aliquots were removed from the continuously shaking cultures of both the ndicated . Samplesp-value cutoff of 0.05 for each metabolite in each strain at each time point. Remaining data were averaged for each time point, strain and metabolite. For a given time point, when a metabolite was not detected in any of the 5 replicates, the minimum value of the metabolite from the remaining data was used as the value for that time point. The log-transformed scaled and centered metabolite measurements were clustered by hierarchical clustering with 6 clusters using the complete linkage method. P-values of significant differences between Δura3 parent strain and the ΔtrmB mutant strain were calculated using a Welch’s two sided T-test at each timepoint for each cluster  were averaged at each time point during the glucose addition time course in the ΔtrmB mutant strain and Δura3 parent strain (n = 20). These measurements were correlated using a linear model to the averaged log-transformed mean-centered and normalized data for guanosine and adenosine measured at the same time points.The log-transformed, mean-centered and normalized time course gene expression data  for geneS1 Figura3 (right) and ΔtrmB (left) data are shown. Cluster 1 is shown in black, cluster 2 is shown in red, cluster 3 is shown in blue, cluster 4 is shown in green, cluster 5 is shown in orange and cluster 6 is shown in yellow.Figure depicts six clusters of metabolite patterns. Logged, mean-scaled and normalized combined Δ(PDF)Click here for additional data file.S2 Figp-value  of the T-test between metabolite levels in the Δura3 and ΔtrmB strains for each of the six clusters of metabolite patterns at each time point. Arrow depicts when glucose was added to a final concentration of 5%.Figure depicts the negative log10 (PDF)Click here for additional data file.S3 Figura3 parent strain (A) and ΔtrmB mutant strain (B) during the glucose addition (black lines), control (dark grey lines), and sucrose control (light grey lines) time course. Cells were grown in Complete Defined Medium (CDM).Mean optical density of 3 biological replicate cultures of the Δ(PDF)Click here for additional data file.S4 FigtrmB mutant and its Δura3 isogenic parent strain in the absence or presence of glucose. Bar plots show log10 gene expression normalized to the Δura3 parent strain in the absence of glucose (data from [ura3 parent strain (dark bars) and ΔtrmB mutant strain (light bars) in the absence and presence of glucose. Error bars represent standard error from the mean of at least 5 microarrays.The expression of the gene encoding adenine phosphoribosyltransferase is similar in both the Δata from ) in the (PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


The ability of hemostatic agents to promote bone repair has been investigated using  In this context, the aim of this study was to compare the potential of bone repair of collagen sponge with fibrin glue in a rat calvarial defect model. Defects of 5 mm in diameter were created in rat calvariae and treated with either collagen sponge or fibrin glue; untreated defects were used as control. At 4 and 8 weeks, histological analysis and micro-CT-based histomorphometry were carried out and data were compared by two-way ANOVA followed by Student-Newman-Keuls test when appropriated (p≤0.05). Three-dimensional reconstructions showed increased bone formation in defects treated with either collagen sponge or fibrin glue compared with untreated defects, which was confirmed by the histological analysis. Morphometric parameters indicated the progression of bone formation from 4 to 8 weeks. Additionally, fibrin glue displayed slightly higher bone formation rate when compared with collagen sponge. Our results have shown the benefits of using collagen sponge and fibrin glue to promote new bone formation in rat calvarial bone defects, the latter being discreetly more advantageous. However, pathological fractures, great bone defects, insufficient blood supply, bone or surrounding tissues infections, and systemic diseases may negatively influence bone healing, resulting in delayed unions or nonunions,Autograft bone is considered the “gold standard” due to the osteoconduction, osteoinduction and osteogenesis promotion as well as angiogenesis without the risk of disease transmission,,,,,-,,Hemostatic agents have been used to control hemorrhage during surgical procedures for harvesting bone grafts from donor sites. Collagen sponge and fibrin glue are employed as hemostatic agents and as scaffolds for bone and cartilage tissue engineering,,In addition to hemostatic properties, it would be interesting if these materials could favor bone repairCollagen sponges , derived from purified skin pig, were cut to produce samples with 5 mm in diameter and 2 mm height. This preparation was carried out in a laminar flow cabinet to keep the material sterile. Fibrin glue , a combination of human fibrinogen, aprotinin and thrombin, was prepared immediately before using according to the manufacturer’s instructions. Solutions of fibrinogen and aprotinin were heated for 10 min at 37°C, mixed and kept for 1 min at 37°C. In another flask, a solution of thrombin was combined with calcium chloride and kept at 37°C. Mixtures of aprotinin with fibrinogen and thrombin with calcium chloride were placed in separate syringes connected by a Y-piece that allowed them to blend immediately before implantation in bone defect.All animal procedures were conducted under approval of the Committee of Ethics in Animal Research of the University of São Paulo. Thirty male Wistar rats weighting 250-300 g were anesthetized by a combination of ketamine (7 mg/100 g body weight)  and xylazine (0.6 mg/100 g body weight) . The cranium of each rat was shaved and disinfected with povidone-iodine alcoholic solution  and an incision was made along the sagittal suture to expose the parietal bones. Unilateral calvarial bone defects with 5 mm in diameter were created with a trephine under saline irrigation to remove both external and internal cortical and to preserving the dura mater. The bone defects were randomly treated  with either collagen sponge or fibrin, or kept empty (control). The skin was sutured with nylon 3.0 . After surgery, the animals received a single dose of antibiotics solution containing benzathine benzylpenicillin (156.000 IU/100 g body weight), benzylpenicillin procaine (78.000 IU/100 g body weight), benzylpenicillin potassium (78.000 UI/ 100 g body weight), dihydrostreptomycin base (65 mg/ 100 g body weight), and streptomycin base (65 mg/100 g body weight)  and flunixin meglumine analgesic (10 mg/100 g body weight) . At the end of 4 and 8 weeks, key time points to determine the progression of bone formation in this animal model, the rats were euthanized and the calvariae harvested and processed for histological and histomorphometric analyses.Harvested calvariae were fixed in 10% buffered formalin for 36 h and decalcified in buffered EDTA  for 10 days. Decalcified tissues were then embedded in paraffin and tissue sections with 6 µm thickness - from the central portion of samples - were stained with hematoxylin and eosin. Histological images were acquired under light microscopy  using a digital camera Axiocam ICc3 (Carl Zeiss) attached to the microscope and processed with the software Axion Vision (Carl Zeiss).Before the decalcification for histological processing, samples fixed in 10% buffered formalin for 36 h, were submitted to micro-computed tomography (micro-CT) for morphometric analysis using the SkyScan 1172 system . Images were acquired at 60 kVp and 200 mA and reconstructed using the software NRecon (Bruker-Skyscan) with smoothing 1, ring artifact correction 5 and beam hardening correction 20%. The micro-CT analyses were carried out using the 3D Ctan software (BruKer-Skyscan) to evaluate bone volume, percentage of bone volume, bone surface and trabecular number, thickness and separation.The results were expressed as mean±standard deviation (n=5) and compared by two-way ANOVA (treatment x time point) followed by Student-Newman-Keuls test when appropriated. The level of significance was set at p≤0.05.Three-dimensional micro-CT reconstructions showed the lack of bone formation inside control defects at 4 and 8 weeks  and J whBone volume  and its This study was designed to evaluate if treatment with either collagen sponge or fibrin glue is able to favor bone formation in rat calvarial defects compared with non-treated defects. The newly formed bone observed was histologically similar irrespective of treatment, in contrast with the lack of detectable bone repair inside control defects. In general, morphometric parameters indicate more bone formation in treated defects when compared with the non-treated ones, with a tendency to be larger in defects treated with fibrin glue.Histological sections are useful to observe and describe morphological features of tissues; however, they do not allow the reconstruction of three-dimensional images from serial sections, as a tissue segment is removed during the sample preparation,,,,In addition to the hemostatic effect, collagen sponge and fibrin glue may affect tissue healing including bone tissue. The use of collagen sponge on perforated cortical model promotes bone augmentation possibly by acting as a scaffold for cells and keeping the space for bone growthIn conclusion, we have shown, by histological and morphometric analyses, the benefits of using collagen sponge and fibrin glue to promote new bone formation in rat calvarial bone defects, with slight advantage to fibrin glue. Thus, these materials could be combined with cells and growth factors as either cell therapy or tissue engineering approaches aiming at enhancing and/or accelerating bone repair.


Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis and no targeted treatments. TNBC patients are more likely to develop metastases and relapse than patients with other breast cancer subtypes. We aimed to identify TNBC-specific genes and genes associated with lymph node metastasis, one of the first signs of metastatic spread. A total of 33 TNBCs were used; 17 of which had matched normal adjacent tissues available, and 15 with matched lymph node metastases. Gene expression microarray analysis was used to reveal genes that were differentially expressed between these groups. We identified and validated 66 genes that are significantly altered when comparing tumours to normal adjacent samples. Further, we identified 83 genes that are associated with lymph node metastasis and correlated these with miRNA-expression. Pathway analysis revealed their involvement in DNA repair, recombination and cell death, chromosomal instability and other known cancer-related pathways. Finally, four genes were identified that were specific for TNBC, of which one was associated with overall survival. This study has identified novel genes involved in LN metastases in TNBC and genes that are TNBC specific that may be used as treatment targets or prognostic indicators in the future. BRCA1 mutation carriers present with TNBC, high mitotic counts, and a high proportion of somatic p53 mutations56Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype. This subtype is characterised by the absence of the estrogen (ER) and progesterone (PR) receptors, and the human epidermal growth factor receptor 2 (HER2/HER neu). Further characteristics of the TNBC subtype are: a high proportion of germline BRCA1 mutation-positive patients diagnosed with TNBC, but not in other TNBC patientsBRCA1 and PARP) in DNA repair, such that if both are functionally inactive DNA damage will not be repaired and the affected cell diesThe absence of the three receptors significantly reduces targeted treatment options for patients with TNBC and the only treatment remains radiotherapy and chemotherapy1microRNAs (miRNAs) are small (18–21 nucleotides) non-coding RNAs, which are able to alter gene expression post-transcriptionally. microRNAs have been found in multiple species, where they are highly conserved, suggesting they play a universal role in the regulation of gene expression. miRNAs regulate multiple biological processes including proliferation, cell death, development, genomic stability, and EMT10There are multiple studies that have shown altered miRNA levels in TNBC patients compared to healthy controls and compared to other breast cancer subtypes131415et al. (2013) identified a number of genes as biomarkers that are associated with survival in TNBC using a series of breast tumours and matched lymph node metastases18The Cancer Genome Atlas (TCGA) TNBC breast cancer cohortA recent study by Cascione et al. 13 identiWe compared the gene expression of 33 grade 3 primary invasive ductal carcinomas (IDCs) to 17 normal adjacent tissue (NAT) samples  to reveaPTGER2, ERBB2, E2F4, and TGFB1  to study gene networks and pathways that involve the genes of interest. All 185 significant genes, with their expression values from the tumour versus normal comparison were used to perform a Core Analysis. This analysis was used to interpret the dataset in the context of biological processes that included pathways, upstream regulators and molecular networks. The analysis revealed that the disorder with the highest number of affected genes was Cancer with 119 out of 185 genes. Multiple genes were involved in the process of Cellular Development (60 genes) and Tissue Development (56 genes). The top upstream regulators of our genes of interest are nd TGFB1 .To validate the genes from the tumour versus normal comparison we used an independent cohort containing 16 TNBC samples, 4 NAT and 48 samples of other breast cancer subtypes . We compWe used our second cohort and the TCGA breast cancer cohort to identify which of the validated genes in each cohort are specific to TNBC. Therefore we performed tumour vs normal comparisons in all non-TNBC cases in both cohorts and compared this to differentially expressed genes in the TNBC cohorts. The results from this analysis are summarised in By performing an IDC versus NAT comparison in our second cohort for all non-TNBC (n = 48) samples and comparing that to the list of genes in the TNBC set (n = 16) we found that, from the 99 validated genes, 28 were found to be differentially expressed in TNBC cases compared to non-TNBC cases, we will refer to these as TNBC specific genes . Figure Further to this, the same analysis was done in the TCGA breast cancer cohort (excluding TNBC samples). We compared the gene expression of 313 non-TNBC cases and 43 matched normal samples from the TCGA breast cancer cohort, this was then compared to the 95 validated genes from the TNBC TCGA cohort. In this analysis, we identified that 14 of the 95 validated genes were differentially expressed solely in the TNBC cohort and not in non-TNBC cases and were hence TNBC specific. ANKRD30A, ANP32E, DSC2, IL6ST) were common to both TNBC cohorts  which contains 55 TNBC samples, of which nine patients died and 46 are still alive. With this information we were able to determine if our 4 TNBC specific genes  were associated with survival. We performed Kaplan-Meier-Analysis on the four genes that are TNBC specific in our second cohort as well as in the TCGA cohort . The results from this analysis can be seen in ANKRD30A, DSC2) show a non-significant trend that low gene expression is associated with shorter survival, ANP32E expression shows no association to survival. High expression of IL6ST shows significant (p = 0.0421) association with better survival outcomes.We used the breast cancer cohort from Gene expression analysis of the 33 primary TNBC tumours, 15 matched lymph node metastases, and 17 matched normal breast tissues was undertaken to identify which transcripts were associated with various aspects of TNBC. The arrays were analysed using Genomic Suite 6.6 (Partek).1: lymph node positive primary tumours (IDC+) versus matched normal adjacent tissue (IDC+ vs NAT+), category 2: lymph node negative primary tumours (IDC-) versus matched normal adjacent tissue (IDC− vs NAT−), and category 3: lymph node metastases versus matched normal adjacent tissue (LNmet vs NAT+)  . The focWe identified 361 genes that were differentially expressed in IDC+ tissue compared to matched NAT (category 1), 92 were differentially expressed in IDC- samples compared to their matched NAT (category 2), and 165 had significantly altered expression in LNmet samples compared to matched NAT samples (category 3). There were 83 genes that were specifically associated with LN metastasis, since they were differentially expressed in category 2 and 3. This included 72 protein coding genes and 11 non-coding RNAs (such as MEG3); out of these 36 had increased expression in IDC+ and LNmet samples compared to NAT+ samples, and 47 showed decreased expression in IDC+ and LNmet samples compared to NAT+ samples .diseases and disorders was Cancer, with 62 genes involved. The majority of these are involved in cellular processes like cell cycle, DNA replication, recombination, repair, and cell death/survival  and inhibited genes . None of these genes were present in the validated TNBC specific gene list but 63% (52 genes) were differentially expressed in tumour versus normal comparisons when all cases were compared in cohort 2 and the TCGA cohort indicating that they may be important biomarkers of metastatic progression in all breast cancers. We also performed survival analysis (using the complete TCGA breast cancer cohort) of the five most up- and five most down-regulated genes from this signature, but were unable to show a significant association to overall breast cancer survival (data not shown).A second Core analysis was performed in IPA with the 83 significant genes that were potential biomarkers for metastasis. Similarly the top candidate for survival . LookingOur previous study identified miRNAs associated with LN metastasisThe outcome for triple negative breast cancer (TNBC) patients is generally considered to be poor. Nevertheless, TNBC is a heterogeneous disease and the probability of survival and/or relapse is different from patient to patient. Specific gene expression patterns can be used to identify differences in patients with phenotypically similar disease but with very different disease outcomes212325MEG3, which has not previously been reported to be associated with metastatic breast cancer.In this study we identified and validated TNBC-specific genes, which we were able to associate with overall survival. Further to this, we have revealed genes associated with lymph node metastasis in TNBC and showed that these are potentially targetable by microRNAs with altered expression. This included the lncRNA gene We compared IDC to NAT samples to identify tumour-associated genes in TNBC. Although, it has been shown that normal tissue adjacent to TNBC tissue has altered gene expression compared to healthy controls, and that NAT samples already show an expression profile indicating DNA repair deficiency27The 185 genes that we identified showed clear hierarchical clustering of NAT samples and IDC samples. The pattern included 90 genes that were significantly up-regulated in all tumour samples and 95 that are significantly down-regulated.We were able to confirm the expression pattern of 66 of the 185 genes in our two validation cohorts (cohort 2 and TCGA), which also allowed us to reveal four genes that are specific for TNBC, by comparing the expression of the validated genes to significantly altered genes in a tumour versus normal comparison in other breast cancer subtypes .ANKRD30A, ANP32E, DSC2, IL6ST  show a non-significant trend that higher gene expression is associated with longer survival time. ANP32E does not show any association with overall survival in TNBC patients. Finally, higher expression of IL6ST shows significant association with longer overall survival in TNBC patients. To the best of our knowledge IL6ST has not been associated with overall survival in TNBC before. Nevertheless, it has been shown to be associated to ER expression and with TNBC development/progression2930These four TNBC specific genes are 2, IL6ST , Table 12, IL6ST . Two of ANKRD30A is well known in breast cancer as NY-BR-1 (Breast Cancer Antigen NY-BR-1)et al. identified the gene in 2001 as a tissue-specific putative transcription factor in breast tissue by serological screening of a breast cancer libraryANKRD30A has been suggested as a potential target for immunotherapy due to its highly restricted expression pattern in breast cancer it may function as a breast differentiation antigenANKRD30A expression is associated with lymph node negativity, as well as with the expression of HER2 and ERANP32E was more highly expressed in TNBC than non-TNBC in our study and has recently been identified as a histone chaperone that removes H2A.Z from chromatin38DSC2, it is part of a six-gene signature predicting breast cancer lung metastasisDSC2 is a Ca2+-dependent transmembrane cell adhesion protein of desmosomeset al., the function of DSC2 has not been studied in breast cancer.IL6ST is the signal transducer for interleukin 6 (IL6), ciliary neurotrophic factor (CNTF), leukemia inhibitory factor (LIF), and oncostatin M (OSM). We showed that IL6ST was lower in TNBC when compared to non-TNBCs. High expression of IL6ST has been shown to be a good prognostic factor in breast cancer as it increases patients overall survivalIL6ST as being positively associated with ER-α expression in breast cancer30APOD, which is a lipocalin. APOD is used as a biomarker indicating good prognosis in colorectal cancer, if its expression level is increased since APOD induces growth arrest and reduces cell proliferation when its levels are elevated4445The second aim of this study was to identify biomarkers associated with metastasis in TNBC. Lymph node metastases are the first sign of metastatic potential. Even though they are not necessarily associated with prognosis, they provide an ideal tissue to gain knowledge about the mechanisms of tumour progression. In this study, we identified genes that are only differentially expressed in the lymph node positive primary tumours and lymph node metastases (NAT+ v IDC+ and NAT+ v LNmet). By doing so, we identified a unique gene pattern of 83 genes that may be potential biomarkers for metastasis in TNBC. The most significantly down-regulated gene in this comparison was HOTAIRMEG3 is known to be down-regulated in multiple cancers and tumour cell proliferation is inhibited by MEG3 expression. It is able to alter the p53 pathway and acts as a tumour suppressor50MEG3 overexpression leads to G2/M cell cycle arrest and apoptosis, which would explain increased cell growth when MEG3 is down-regulatedMEG3 activates autophagy, which leads to increased cell proliferationMEG3 in triple negative breast cancer is unknown and needs further investigation.We identified 72 protein coding genes and 11 non-coding RNA (ncRNA) to be associated with lymph node metastasis. The discovery that not just changes in protein coding genes but also in non-coding genes are responsible for cancer development and cancer progression has transformed cancer research in recent yearsSPP1, TOP2A, AREG, EGR1, CD34, and IGF1) as well as one of the identified miRNAs (hsa-miR-101), that they found to be differentially expressed in lymph node metastases compared to primary tumours and to normal tissue. Another miRNA-mRNA integration study in breast cancer by Buffa et al. found three miRNAs  to be associated with progression pathways in TNBCet al.In our previous study we used this TNBC cohort to identify microRNAs (miRNAs) that were associated with lymph node metastasisTOP2A is the gene with the highest fold change in our cohort . This gene encodes an enzyme that is important for chromosome condensation, chromatin separation during DNA replication. Over-expression of this gene is a known prognostic marker for poor outcome in several malignancies, including TNBC5859TOP2A is associated with worse prognosis, it also provides knowledge about the efficacy of treatment since TNBC patients with high TOP2A expression respond better to anthracycline therapyWe were unable to associate the five most up- and five most down-regulated genes to overall survival in the TCGA cohort. Nevertheless, there are a number of genes within our list of 83 genes, associated to lymph node metastasis, that have been associated with prognosis in other studies. TPX2, TOP2A, UBE2C, MELK, RAD51AP1, MAD2L1, ATAD2, CKS2, ECT2, GPI, STAT1, CXCL9, CXCL10, CXCL11, SMS, and TNFRSF13B. All of the genes are up-regulated in our cohort, suggesting a poor outcome for the patients and possible aneuploidy. The study from Carter et al. (2006) shows that the gene with the highest level of consistent correlation with total functional aneuploidy is TPX2 which has been supported by Szasz et al. (2013) who used a gene set of 4 CIN genes to measure tumour aneuploidy, two of them are TOP2A and TPX2A recent study performed a meta-analysis of global gene expression profiles of TNBC to identify genes of prognostic value62In conclusion, we identified TNBC-specific gene expression profiles and showed novel associations for TNBC-specific genes to prognosis. Additionally, we identified a gene expression profile for genes associated with lymph node metastasis, which we were able to correlate our previous study results of microRNA expression profiles with the profiles of this study. In this way we identified novel microRNA and mRNA interactions, supporting important pathways in TNBC development.National Statement on Ethical Conduct in Research Involving Humans.A total of 33 grade 3, triple negative, invasive ductal carcinomas (IDCs), 17 matched normal adjacent tissues (NAT), and 15 lymph node metastases (LNmet) were used for gene expression microarray analysis. All samples were formalin-fixed, paraffin-embedded (FFPE) and obtained from the archives of the Hunter Area Pathology Service, John Hunter Hospital, Newcastle, Australia. This cohort has been described previouslyThe RNA extraction of all samples was performed as previously describedThe array results have been deposited in Gene Expression Omnibus (GEO) with Accession No. GSE61725.100 ng total RNA of all FFPE samples was amplified (Ovation FFPE WTA kit) and biotinylated (Encore Biotin module) according to the manufacturers’ instructions . The samples were hybridised to HuGene 2.0 arrays  and 17 hours later washed and stained. The Arrays were scanned on a GeneChip Scanner 3000 7G (Affymetrix).The HumanGene 2.0 arrays (Affymetrix) contain probe features representing 11,000 lncRNAs, 24,000 genes, and 30,000 coding transcripts. The data was imported to Genomic Suite 6.6 (Partek) and a robust multi-array analysis (RMA) was performed, which included log2 transformation, background correction, quantile normalisation and summarisation of the probe features resulting in a set of expression signal intensities.Unsupervised hierarchical clustering was performed on genes that were found to be significantly different in the comparison of all IDC vs all NAT samples . Correction for multiple testing was performed using Benjamini–Hochberg procedure.We compared gene expression in three different categories. Category 1: invasive ductal carcinoma with lymph node metastases versus normal adjacent tissue from patients with lymph node metastases (IDC+ vs NAT+), category 2: IDC- vs NAT-, and category 3: lymph node metastases (LNmet) vs NAT+  . This study complies with the Helsinki Declaration with ethical approval from the Hunter New England Human Research Ethics Committee . A waiver of consent was granted for this study in accordance with the The samples and the method of RNA extraction have been described previouslyFor further validation of the tumour vs normal comparison as well as the identification of TNBC specific genes we used the The Cancer Genome Atlas (TCGA) breast cancer cohort gene expression dataWe performed Kaplan-Meier analysis on the validated TNBC specific genes that we identified. Therefore we used the median gene expression to divide the patients into high and low expression and together with the TCGA survival data we were able to perform the analysis using GraphPad Prism 6 survival analysis tool. P-values were calculated using the log-rank (Mantel-Cox) method and hazard ratios were calculated by the Mantel-Haenszel method.Differentially expressed transcripts were imported with their expression values into Ingenuity Pathway (IPA), where a Core Analysis was performed to identify their involvement in biological processes, pathways and molecular networks.To determine if altered microRNA expression contributed to the identified gene expression profiles, we correlated differentially expressed genes to microRNA microarray expression data from the same sample cohort, a previously published studyPartek Genomics Suite 6.6 was used to identify microRNAs that were differentially expressed in lymph node metastases and lymph node positive primary tumours but not in lymph node negative tumours, compared to matched NAT samples. Significance was reached with p-values <0.05 and two-sided fold change >1.5, these parameters identified 22 microRNAs see . CorrectThese microRNAs were correlated to significantly altered genes identified in this study. The correlation was performed in Partek Genomic Suite 6.6. Pearson Correlation and Spearman’s rank correlation were used to correlate microRNAs with potential target genes. These correlation analyses include the microRNA and gene expression values as well as two target prediction software suites .t-test and ANOVA were used to analyse differences between two or more groups. Significance was regarded for p < 0.05 and two-sided fold change >1.5.Student’s How to cite this article: Mathe, A. et al. Novel genes associated with lymph node metastasis in triple negative breast cancer. Sci. Rep.5, 15832; doi: 10.1038/srep15832 (2015).


Three NDM positive clonally unrelated clinical isolates of P. aeruginosa were recovered from hospital patients. Association of integron with blaNDM-1 and presence of gene cassettes were assessed by PCR. Genetic linkage of NDM gene with ISAba125 was determined and in negative cases linkage in upstream region was mapped by inverse PCR. In which only one isolate’s NDM gene was linked with ISAba125 for mobility, while other two reveals new genetic arrangement and found to be inserted within DNA directed RNA polymerase gene of the host genome detected by inverse PCR followed by sequencing analysis. In continuation significance of this novel linkage was further analyzed wherein promoter site detected by Softberry BPROM software and activity were assessed by cloning succeeding semi-quantitative RT-PCR indicating the higher expression level of NDM gene. This study concluded out that the unique genetic makeup of NDM gene with DNA-dependent-RNA-polymerase favours adaptability to the host in hospital environment against huge antibiotic pressure.New Delhi metallo β-lactamases are one of the most significant emerging resistance determinants towards carbapenem drugs. Their persistence and adaptability often depends on their genetic environment and linkage. This study reports a unique and novel arrangement of  Pseudomonas spp. [The New Delhi Metallo-β-lactamase (NDM) has emerged as a major carbapenemase with rapid dissemination worldwide . Clinicanas spp.  which exnas spp. . Most imblaNDM among promiscuous plasmids is the major dissemination route including clonal outbreaks. Noticeably, blaNDM has been frequently identified from unrelated gram negative bacilli, harboured by different plasmid types [blaNDM can be carried by different plasmid types  and occasionally found to be chromosomally integrated [blaNDM are now available and reveals its inimitable genetic features such as association with insertion sequences and transposons for high mobility, acquisition of other multiresistance regions  including additional important enzymes which make it more versatile [Transfer of the id types . Howevertegrated . The seqersatile .blaNDM gene among clinical isolates along with other resistance factors. However, this novel finding suggests the insertion of blaNDM within DNA directed RNA polymerase gene, thus favouring its survivability within hospital.In this study we have presented a unique genetic makeup of P.aeruginosa were collected from indoor patients of Sir SunderLal Hospital, Banaras Hindu University, Varanasi, India, during March 2011 to September 2011. Identification of organisms was done by the conventional methods [A total of 105 consecutive, non-duplicates, carbapenem non-susceptibile isolates of  methods .E. coli harbouring blaNDM was taken as positive control [E. coli ATCC 25922 was used as negative control.The metallo β-lactamase status of the strains was established by the Imipenem—Ethylene diamine tetra-acetic acid (EDTA) disc potentiation method . A previ control  and E. cAll MBL positive isolates were suspended in 1mL of buffered peptone water supplemented with 30% glycerol (peptone glycerol) and were kept at −80°C. The isolates were also stored in minimal media  as stab culture. ERIC-PCR was performed for genotyping by using their respective primers to determine clonal relatedness of the isolates [This work and obtained samples specifically for this study has been ethically approved by the chairperson of the ethical committee of Institute of Medical Sciences, Banaras Hindu University, Varanasi; Ref. No.-Dean/2012-13/114.blaNDM was performed by PCR assay in all the MBL positive isolates. Reaction conditions and primers used for PCR amplification were as described earlier [integrase, and 288 bp fragment for class 2 integrase. The primers, PCR conditions and reaction mixtures used were as described previously [blaNDM gene with integrons, PCR was performed using forward primer of the conserved region (5’CS) of integron gene and reverse primer of the characterized blaNDM gene [Genomic DNA for PCR was extracted by using QIAamp DNA mini kit . Genotypic detection of  earlier . Consecueviously . To findNDM gene . IntegroNDM gene .Aba125 (Acinetobacter specific), and reverse primer of NDM gene. The reaction mixture and running conditions were as described earlier [Insertion sequences (IS), one of the major genetic elements in transposition of antibiotic resistance genes. In order to assess the linkage of NDM gene with the insertion sequence in our study, PCR analysis was performed by using forward primer of IS earlier .blaNDM-1 gene (apart from their linkage with ISAba125 and integrons) inverse PCR was performed. DNA was extracted from the three strains and digested with Sau3AI . DNA fragments obtained were then autoligated at 16°C with T4 DNA ligase in higher dilution to allow self circularization. The fragment of DNA containing the blaNDM-1 gene was used as a template for an inverse PCR with primers designed from the blaNDM-1 gene sequence. Inv1F as forward and Inv1R as reverse primer [In order to determine the genetic environment surrounding the e primer  were useOnce the sequence of amplified product of inverse PCR was obtained, the linkage was confirmed by using POL’F 5′ACGTCAGAGCGATGAAGACG-3′ as forward primer and Inv1R 5′AATCGTCGGGCGGATTTCACC-3′ as reverse primer to detect 5’ region of target site, followed by second PCR reaction with NDM 3PF 5′GATCGTGATGAGCCATTCCGCC3′ as forward primer and POL’R 5′GACCTGGAACTGACCGTACG3′ as a reverse primer to confirm 3’ target region. To, further establish this linkage, the PCR reaction was performed using POL’F as forward and POL’R as reverse primer among NDM positive isolates.blaNDM probe labelled with DIG HIGH PRIME LABELING MIX  detection Kit. The digoxigenin-labeled blaNDM specific probe was prepared using primers (Forward NDM 5′GGGCAGTCGCTTCCAACGGT 3′ and Reverse 5′CGACCGGCAGGTTGATCTCC 3′) that amplify a 130 bp region of the blaNDM gene. Total genomic DNA was digested by HindIII for fragmentation of DNA which is followed by the transfer to nylon membrane  and then hybridised with prepared blaNDM specific probe. Detection was performed by using an NBT color detection kit. . Promoter activity was assessed by designing two sets of primers; in first set forward primer (RNAPROM) was designed from upstream region of the RNA polymerase promoter whereas in the second set the primer with desired mutation was generated (MUTPROM) in the promoter region. For both the sets the reverse primer used was NDMc [GEM-T vector  in E. coli JM107. Further, RNA was isolated from both the constructs using RNeasyR Mini Kit  and cDNA was prepared using Quanti Tect Reverse Transcription kit . Thereafter, Semi quantitative reverse transcriptase PCR was performed to determine the expression of blaNDM in both the constructs.Simultaneously, to validate our study Southern blotting was performed on agarose gel by in-gel hybridization  with thewas NDMc . The PCRblaNDM was investigated by transformation assay. Conjugation experiment was carried out between clinical isolates as donors and streptomycin resistance E.coli recipient strain B . Overnight culture of bacteria were diluted in Luria Bertani broth  and was grown at 37°C till the O.D. of the recipient and donor culture reached 0.8–0.9 at A600. Donor and recipient cells were mixed at 1:5 donor-to-recipient ratios and transconjugants were selected on imipenem (0.25mg/L) + streptomycin (1000mg/L) agar plates. Transformation was carried out using E.coli JM107 as recipient. Transformants were further selected on imipenem (0.25mg/L) containing LB agar plates.Horizontal transferability of blaNDM as well as in blaNDM harbouring donor strains, PCR based replicon typing was carried out targeting 18 different replicon types [blaNDM positive isolates on LB broth without any antibiotic pressure. After each passage the isolates were tested for the presence of blaNDM PCR assay.For the detection of incompatibility group type of plasmid in transformants with on types . PlasmidblaIMP and blaVIM, as well as ESBLs, AmpC and class D carbapenemase  genes by multiplex PCR [To investigate the presence of other resistant determinants along with NDM, isolates were further tested for the co-existence of other MBL genes such as plex PCR –23. In aplex PCR . Consequplex PCR .Escherichia coli ATCC 25922 was used as a control.Antimicrobial sensitivity testing was performed on Mueller-Hinton agar  plates by Kirby Bauer disc diffusion method and interpreted as per CLSI recommendations . The anthttp://www.ncbi.nlm.nih.gov/BLAST/). Further, promoter sites were also determined by using Soft Berry BPROM software (http://linux1.softberry.com/berry.phtml?topic=bprom&group=programs&subgroup=gfindb).All the PCR amplicons were purified using the QIAquick Gel Extraction kit  and were subjected to DNA sequencing . Sequences were analyzed using the BLAST suite of programs. . Further, class 1 integron was detected among the 99/105 (94.28%) isolates. None of the study isolates were found carrying class 2 integrase. On performing the ERIC PCR for all the 105 isolates a total of 46 different clonal types were observed. However two non MBL strains were found to be clonal with PA47.Among the 105 isolates, 38 strains exhibited MBL activity by Imipenem EDTA disc potentiation method, of which three nonclonal isolates  were found to harbour laNDM-1  and weredhfr) and aminoglycoside acetyl transferase (aac(6’)) within the gene cassette. While analysing the upstream linkage of NDM gene with ISAba125, isolate PA6 formed a band of 850 bp thus showing the association between them which was confirmed by sequencing. However, in case of PA38 and PA47 inverse PCR result gave a novel finding that blaNDM gene got integrated within DNA dependent RNA polymerase of host genome. This was further confirmed by designing primers which could amplify both 5’ and 3’ region of the insert  was present in other two isolates (PA38 and PA47). So, this plasmid could play the role of carrier for their acquisition of resistant determinant which later got integrated within the host genome.Among the carbapenemases, the NDM gene has gained particular attention due to its global dissemination and multidrug resistance phenotype . In the nobactam , 28. Besom India . HoweverAcinetobacter baumannii and is linked with ISAba125 in the upstream region. However, during horizontal transfer the gene got excised from the Acinetobacter DNA along with whole or truncated portion of ISAba125 [Acinetobacter specific primer was used for the study and it was observed that only PA6 showed the presence of this insertion sequence in the upstream area. But acquisition of blaNDM within the DNA dependent RNA polymerase of host chromosome is quite unique and not reported previously.In the previous study it was reported that the NDM gene has originated from ISAba125 . TherefoblaNDM under the control of RNA polymerase promoter might be responsible for higher level of expression, which could probably be the explanation for high MIC of PA38 and PA47.The new genetic makeup of blaNDM is currently higher worldwide due to its potential transferability. As our findings also suggest that the unique genetic makeup of blaNDM is for make an ease to endure the isolate within hospital environment to counter increasing antibiotic pressure. This is an important consideration that Pseudomonas with recombinant blaNDM is crucial for the hospital infection management and therapeutic options, otherwise this new genetic adaptability will lead in to more serious public health implications. From the study it cannot be truly predicted whether this recombination was a by chance event or a true event since the sample size was too small. Therefore, further investigation is advocated to establish this fact.The clinical challenge posed by