Decreased expression of these receptors was associated with functional defects, such as reduced NK degranulation capacity when challenged with the tumor target cell line K562 . This defect could be restored in vitro by stimulating NK cells from T2D patients with IL-15 (P<0.05). NKG2D expression was found to be negatively correlated with HBA1c level , suggesting that sustained hyperglycemia could directly influence NK cell defects. We demonstrated that endoplasmic reticulum (ER) stress, an important mediator in diabetes-associated complications, was inducible in vitro in normal NK cells and that tunicamycin treatment resulted in a significant decrease in NKG2D expression (P<0.05). Furthermore, markers of the Unfolded Protein Response (UPR) BiP, PDI and sXBP1 mRNAs were significantly increased in NK cells from T2D patients , indicating that ER stress is activated in vivo through both PERK and IRE1 sensors. These results demonstate for the first time defects in NK cell-activating receptors NKG2D and NKp46 in T2D patients, and implicate the UPR pathway as a potential mechanism. These defects may contribute to susceptibility to infections and malignancies and could be targetted therapeutically.Patients with Type 2 diabetes (T2D) are highly susceptible to infection and have an increased incidence of some tumors, possibly due to immune system dysfunction. In the innate cellular immune system, Natural Killer (NK) lymphocytes are important effectors responsible for controlling infections and combating tumor development. We analyzed NK cell subsets in 51 patients with long-standing T2D. Compared with healthy blood donors, diabetic patients showed a profound decrease in both NKG2D-positive NK cells (44%  For instance, acute hyperglycemia has been shown to reduce neutrophil degranulation in healthy subjects Clinicians are well aware that patients with type 2 diabetes (T2D) are highly susceptible to infections and are prone to malignancy Mycobacterium tuberculosis, or Escherichia coli) and oxidative stress NK cells have the machinery to recognize and deal with both tumors and viral or bacterial infections, all of which are prevalent in T2D. Their activity is regulated by activating receptors, including NKp30, NKp44, NKp46, NKG2C and NKG2D, which all bind ligands present at the surface of tumors or infected cells Hyperglycemia is prominent with T2D and has been shown to impair ER functions, leading to the accumulation of misfolded proteins in the ER lumen and promoting ER stress The aim of the current work was to establish the potential role of NK cell abnormalities in the immune dysfunction observed in T2D patients. Our data show for the first time that T2D patients have a decreased frequency of both NKp46 and NKG2D-positive NK cells. Down-regulation of NKG2D on NK cells was also more pronounced in patients with uncontrolled hyperglycemia and appears to be linked to ER stress.Type 2 diabetic patients included in the study were regularly followed as out-patients in the Endocrinology Unit in our hospital. Inclusion criteria were as follows: patients older than 18 years with a diagnosis of T2D. Exclusion criteria included a history of malignancy, chronic or acute hepatitis B or C, or HIV infection, previous or current immunosuppressive treatments and current infection. Clinical data were obtained from medical files. Renal function was estimated by the MDRD equation Lymphocyte immunophenotyping was performed on frozen samples of PBMCs by eight-color analysis using a flow cytometer (Canto II) from BD Biosciences . Samples were fixed with PBS containing 2% paraformaldehyde. The following antibodies were used for the analysis: fluorescein isothiocyanate (FITC)-conjugated anti-KIR2DL2 ; phycoerythrin (PE)-conjugated anti-NKp30 (clone Z25), anti-NKp44 (clone Z231), anti-NKp46 (clone BAB281), anti-NKG2C (clone 134591), anti-KIR2DL1DS1  and anti-KIR2DS4 ; peridinin chlorophyll protein (PerCP)-conjugated anti-CD8 (clone SK1); allophycocyanin (APC)-conjugated anti-NKG2D (clone ON72), anti-NKG2A (clone Z199), and anti-KIR3DL1 ; biotin-conjugated anti-CD56 (clone B159) used with streptavidin-PE-Alexa Fluor 750; allophycocyanin-H7 (APC-H7)-conjugated anti-CD16 (clone 3G8), AmCyan-conjugated anti-CD3 (clone SK7) and Pacific Blue-conjugated anti-CD4 (clone RPA-T4).bright CD16dim/neg and CD3-negative CD56dim CD16bright NK populations. The frequency of positive cells and the level of expression of the fourth marker in each subset were evaluated using the DIVA software . To monitor the induction of cell death, NK cells were stained with fluorescein isothiocyanate-conjugated Annexin V  according to the manufacturer’s instructions.Products were purchased from Beckman Coulter , Becton Dickinson Biosciences , R&D Systems Inc . All flow cytometry analyses were performed using a combination of CD3, CD16, and CD56 antibodies along with a fourth antibody to specifically gate either CD3-positive T lymphocytes or the CD3-negative CD56The correspondance between colors and specificities is shown in supplemental data. .PBMCs from diabetic patients and healthy donors were isolated from 15 ml of fresh whole blood by density gradient centrifugation using lymphocyte separation medium . PBMCs were stored in liquid nitrogen prior to phenotypic and functional analysis. When necessary, NK cells were then isolated from PBMCs by negative selection using an NK Cell Isolation Kit II  according to the manufacturer’s instructions.Frozen PBMCs and isolated NK cells were thawed in RPMI 1640 containing 10% FBS. Where indicated, IL15  was added to NK cell cultures for 16 hours. Cells were harvested and stained with appropriate antibodies for flow cytometry analysis. PBMCs from healthy donors were cultured with tunicamycin  for 6 hours where indicated. Cells were harvested and stained with appropriate antibodies for flow cytometry analysis, or were lyzed in TRI-reagent .The K562 cell line, used as a target in degranulation assays, was maintained in RPMI 1640 containing 10% FBS.A CD107a degranulation assay was used to assess functional activity of NK cells, as described T method with GAPDH and RPL13A as reference genes and cloned PCR products as calibrators. The primer sequences are listed in Depending on the experiment design, either purified NK cells or PBMCs were used for Real Time quantitative PCR assays. PBMCs were thawed and cultured in RPMI 1640 containing 10% FBS for 6 hours with or without tunicamycin (1.25 µg/mL). Cells were lysed in TRI-reagent , and total RNA was isolated according to the manufacturer’s instructions. Reverse Transcription was performed using the Superscript III First-Strand Synthesis System for RT-PCR . NKG2D, NKp46, ATF4, BiP, CHOP, GADD34, GRP94, HERP, PDI, sXBP1 mRNAs, as well as the reference GAPDH and RPL13A mRNAs were assayed using fluorescence-based real time PCR. Real-time PCR was performed on an ABI PRISM 7000 sequence Detection System with SYBR Green reagents . After initial denaturation (95°C for 10 min), 40 cycles of a two-step PCR (15 s at 95°C and 1 min at 60°C) were performed. Relative expression was calculated based on the ΔΔCg. The resulting serum samples were transferred to polypropylene microtubes and stored at –80°C prior to analysis. Samples were thawed at room temperature before assaying serum levels of sMICA using commercial MICA enzyme-linked immunosorbent assay kits , and serum circulating IL15 was determined using commercially available IL15 enzyme-linked immunosorbent assay kits . The assay was performed according to the manufacturer’s instructions and as previously described Serum was obtained by centrifuging blood samples at room temperature for 15 min at 300×Results are shown as the median value (range). Data were tested for inter-group statistical significance using Wilcoxon’s test for paired variables, or the Mann-Whitney U test for unpaired variables. Correlations were assessed using Spearman’s correlation coefficient. All tests were two-sided, and P<0.05 was considered as the threshold for a significant difference.2). White cell counts were normal, as were total lymphocyte counts .The study population comprised 51 T2D patients and 54 age-matched healthy donors. The demographic breakdown for the diabetic patients is shown in + T cells and on NK cells. In samples from diabetic patients compared to samples from healthy blood donors, the frequency of NKG2D-expression on CD8+ T cells was not modified; however it was significantly lower on NK cells from diabetic patients when compared to healthy blood donors , as shown in vs. 50%, P<0.01; To determine whether certain immune cell populations were altered in T2D patients, we first extensively immunophenotyped peripheral blood lymphocytes. No difference was observed between T2D patients and control patients for total NK cells, CD4-positive cells, CD8-positive T cells and memory T cell (CD45RO+) frequencies (data not shown). Because we suspected a role for NK cells in the T2D phenotype, we next focused on specific NK cell receptors : NKG2D, brightCD16neg/low and CD56dimCD16-positive . CD56bright NK cells tend to produce more cytokines, while CD56dim cells, the major subset at the periphery, are tend to display cytolytic activity bright and CD56dim NK subpopulations was detected in diabetic patients .One of the ligands of NKG2D is MICA, which exists in a soluble and a cell-bound form. The lower frequency of NKG2D-positive NK cells in T2D patients could be linked to increased soluble MICA production. To test this, we assayed serum MICA concentrations. No difference between diabetic and control groups was found  . Such a vs. 15.8+/−1.4%, P<0.05; vs. 64.9+/−4.6% P<0.05; vs. 37.1% +/−6.2, P<0.05; To evaluate the functional properties of diabetic NK cells, we tested their ability to degranulate in the presence of target cells. Lysosomal-associated membrane protein-1 (LAMP-1 or CD107a) has been described as a marker of NK cell degranulation following stimulation . Interestingly, NKG2C mRNA expression was also unaffected in samples from diabetic patients (data not shown).To further characterize the mechanisms resulting in reduced expression of NKG2D and NKp46 in T2D patients, NKG2D and NKp46 mRNAs were quantified by quantitative real-time PCR in NK cells from both healthy controls and diabetic patients. NKp46 mRNA expression was significantly decreased in diabetic patients compared to healthy donors P<0.05; . In contvs. 64.3% +/−3, P<0.05  and NKG2C expression (4.8% +/−0.8 vs. 6.0% +/−0.8 ns) were not significantly affected by tunicamycin treatment (+ T cells (data not shown). This suggests that ER stress may be involved in the reduced NKD2D levels observed for NK cells from T2D patients.Since NKG2D mRNA was not under-expressed in NK cells from T2D patients, we hypothesized that ER stress could be involved in reducing cell-surface expression of NKG2D. To test this, we first incubated normal PBMCs in the presence or absence of 1.25 µg/mL tunicamycin, which is known to induce the UPR response, and thus ER stress. ER stress marker mRNAs were quantified by real-time PCR, and revealed overall ER stress to be induced : BiP, HE, P<0.05 . NKp46 ereatment . TunicamTo confirm the relevance of these in vitro data, NK cells from T2D patients were tested for ER stress markers . In NK cEpidemiological data shows that T2D is a rapidly growing public health problem NK cells play a crucial role in controlling infections and tumors, but little data is available on this cell subset in T2D patients. In this study, we report that T2D patients have an abnormal NK cell phenotype with a significant decrease in frequency of both NKp46- and NKG2D-positive NK cells. NKp46 is a specific NK receptor which recognizes various influenza hemagglutinins and as yet unknown tumor ligands In addition to decreased expression of both NKG2D and NKp46, functional defects were observed for the NK cell population in T2D patients, which showed reduced degranulation. Our results therefore show altered NK cell phenotype and function in T2D patients compared to age-matched healthy blood donors. These observations could partially explain why T2D patients are more at risk for both infection and cancer.The litterature presents contradictory results with regard to NKG2D expression on cells from patients with diabetes. A decreased frequency of both NKp46 and NKG2D receptors was previously described in a cohort of type 1 diabetic patients In the present study, we propose that sustained hyperglycemia itself, which is the hallmark of diabetes, could be directly or indirectly responsible for some of the NK cell defects observed in T2D patients. In corroboration of this hypothesis, blood HbA1c levels correlated strongly with reduced NKG2D expression in T2D patients. HbA1c is considered to be a good marker of how well diabetes was controlled over the three months preceding its quantification. The correlation between this marker and the frequency of NKG2D-positive cells suggests that the NK cell alterations observed may be directly related to high glucose levels. As the incidence of various infections is associated with episodes of severe hyperglycemia, our results offer a possible mechanistic explanation for this association.In our study, NKp46 down-regulation appears to be transcriptionally-controlled, whereas NKG2D expression is controlled post-transcriptionaly in T2D patients. Since recent evidence suggests that hyperglycemia-induced cell dysfunction may occur as a result of increased ER stress Having observed these NK cell defects, we wished to determine whether they were reversible. To address this, diabetic NK cells were incubated in the presence of IL-15, a key cytokine for NK cell maturation, which is known to increase NKG2D surface expression In conclusion, our results demonstrate that specific NK cell defects could be directly linked to the diabetic milieu. These defects could in turn be linked to the secondary pathologies associated with T2D, infection and neoplasia. This study also highlights the role of metabolic disorders on NK cell dysfunction, especially on the NKG2D/ligand axis. This is a novel field of investigations with a wide medical impact. Pertinently, Xia et al. recently documented the role of NKG2D in atherosclerotic plaque formation Table S1Antibodies and colors used for FACS experiments.(DOC)Click here for additional data file.Table S2Primer sequences used for RT-PCR analysis.(DOC)Click here for additional data file.


Seven linker histone H1 variants are present in human somatic cells with distinct prevalence across cell types. Despite being key structural components of chromatin, it is not known whether the different variants have specific roles in the regulation of nuclear processes or are differentially distributed throughout the genome. Using variant-specific antibodies to H1 and hemagglutinin (HA)-tagged recombinant H1 variants expressed in breast cancer cells, we have investigated the distribution of six H1 variants in promoters and genome-wide. H1 is depleted at promoters depending on its transcriptional status and differs between variants. Notably, H1.2 is less abundant than other variants at the transcription start sites of inactive genes, and promoters enriched in H1.2 are different from those enriched in other variants and tend to be repressed. Additionally, H1.2 is enriched at chromosomal domains characterized by low guanine–cytosine (GC) content and is associated with lamina-associated domains. Meanwhile, other variants are associated with higher GC content, CpG islands and gene-rich domains. For instance, H1.0 and H1X are enriched at gene-rich chromosomes, whereas H1.2 is depleted. In short, histone H1 is not uniformly distributed along the genome and there are differences between variants, H1.2 being the one showing the most specific pattern and strongest correlation with low gene expression. Eukaryotic DNA is packaged into chromatin through its association with histone proteins. The fundamental repeat unit of chromatin is the nucleosome, which consists of 146 bp of DNA wrapped around an octamer of core histone proteins H2A, H2B, H3 and H4. Linker histone H1 sits at the base of the nucleosome near the entry and exit sites and is involved in the folding and stabilization of the 30-nm chromatin fiber, allowing a higher degree of DNA compaction . HistoneUnlike core histones, the H1 histone family is more evolutionary diverse and many organisms have multiple H1 variants or subtypes, making the study of these proteins more complex. In humans, the histone H1 family includes 11 different H1 variants with 7 somatic subtypes , three testis-specific variants  and one oocyte-specific variant (H1oo). Among the somatic histone H1 variants, H1.1 to H1.5 are expressed in a replication-dependent manner, whereas H1.0 and H1X are replication-independent. H1.2 to H1.5 and H1X are ubiquitously expressed, H1.1 is restricted to certain tissues, and H1.0 accumulates in terminally differentiated cells .It is still far from clear why there are so many H1 variants and great efforts have been made recently to elucidate whether they play specific roles or have redundant functions. Single or double H1 variant knock-out studies in mice did not identify any specific phenotype and this was attributed to the compensatory upregulation of other subtypes, favoring the view that there is redundancy between H1 variants . Despitein vivo. Initial biochemical and microscopy-based approaches suggested a nonuniform distribution of H1 in the cell nucleus and found differences between variants  combined with quantitative polymerase chain reaction (qPCR), tiling promoter arrays and high-resolution sequencing. We combined the use of specific antibodies for some variants and hemagglutinin (HA)-tagged recombinant H1 variants expressed in cell lines to study the genome-wide distribution of H1.0, H1.2 to H1.5 and also H1X, a more recently identified and distantly related H1 variant. H1.1 was omitted from our analysis, it being the only somatic H1 variant not present in many cell types, including the cells used here. We also compared H1 distribution with the nucleosome distribution in our T47D human breast cancer cell lines, by H3 immunoprecipitation. Our data support the view that all H1 variants occur across the genome, but also uncover specific features for H1.2, both at promoters and genome-wide. Interestingly, H1.2 enrichment correlates the most closely with gene repression, structural domains of chromatin such as lamina-associated domains (LADs) and regions of low GC content. Overall, the distribution of H1.2 along chromosomes differs from that of other variants including H1.0 and H1X, the two variants most structurally distant within the somatic H1 family. This work represents a comprehensive attempt to investigate for the first time the occurrence and relevance of the different histone H1 variants in the genome of human cancer cells, and provides valuable data to clarify our understanding of the functionalities and heterogeneity of H1.2 in RPMI 1640 medium, supplemented with 10% FBS, 2 mM l-glutamine, 100 U/ml penicillin and 100 µg/ml streptomycin, as described previously  and 1% penicillin/streptomycin. MCF7 cell line was grown at 37°C with 5% CO2 in Minimum Essential Medium (MEM) medium containing 10% FBS, 1% penicillin/streptomycin, 1% nonessential amino acids, 1% sodium pyruvate and 1% glutamine.Breast cancer T47D-MTVL cells (carrying one stably integrated copy of luciferase reporter gene driven by the MMTV promoter), or derivative cells stably expressing HA-tagged H1 variants (H1-HA), were grown at 37°C with 5% COeviously . HeLa ceFor Phorbol myristate acetate (PMA) experiments, serum-containing Roswell Park Memorial Institute (RPMI) 1640 media was replaced by serum-free media. After 24 h under serum-free conditions, cells were treated with PMA (100 nM) for the indicated time at 37°C.Generation of T47D-MTVL stably expressing HA-Tagged H1 variants was achieved as described previously . BrieflyChIP assays were performed as described previously . BrieflyThe following antibodies were used in this study: anti-H1.2 (Abcam 4086), anti-H1X (Abcam 31972), anit-H3 (Abcam 1791) and anti-HA tag (Abcam 9110).Real-time PCR was performed on ChIP and input DNA using EXPRESS SYBR GreenER qPCR SuperMix Universal (Invitrogen) and specific oligonucleotides in a Roche 480 Lightcycler. ChIP values were corrected by the correspondent input chromatin sample. All oligonucleotide sequences used for the amplifications are available on request.At least 10 ng of ChIP and input DNA was amplified using GenomePlex Complete Whole Genome Amplification Kit (Sigma) and eluted with GenElute PCR Clean-Up Kit (Sigma). For ChIP-on-chip experiments we used Nimblgen HG18 Refseq Promoter 3x720K array. One microgram of ChIP and input DNA was directly labeled by Klenow random priming with Cy5 and Cy3 nonamers with Nimblegen Dual-color DNA Labeling Kit following manufacturer's user's guide Chip-chip arrays v6.2, and the labeled DNA was precipitated with 1 volume isopropanol. Hybridization mix including 15 µg of labeled DNA was prepared using Nimblegen Hybridization Kit. Arrays were hybridized in Nimblegen Hybridization System 4 Station for 16–18 h at 42°C, and then washed in 1× Wash solution I, II and III. Hybridization buffers and washes were completed using manufacturer's protocols. Arrays were scanned on a Nimblegen MS 200 Scanner per manufacturer's protocol.ChIP-on-chip raw data was normalized and differential intensity of each probe compared with input control was calculated using the Nimblegen software DEVA. Average fold change (ChIP versus input) each 50 bp bin for a range of −3.2 kb upstream and 800 bp downstream window from RefSeq transcription start sites (TSS) were calculated using in-house Perl script. LOESS smoothed line plot around the TSS were plotted using in-house script written in R statistical programming language. For ChIP-signal heat map, similarly fold change average for each individual RefSeq transcript was calculated and then data were visualized with Java Treeview . FunctioLibrary preparation for sequencing: ChIP and genomic library preparation was performed using standard Illumina protocols. Libraries were prepared with the ChIP-seq Sample Preparation Kit (Illumina) according to the manufacturer’s instructions. Briefly, 10 ng of ChIP and input DNA were repaired to overhang a 3′-dA and then adapters were ligated to the end of DNA fragments. DNA fragments with proper size  were selected after PCR amplification, obtaining qualified library for sequencing.Supplementary Table S1. Peak caller program for histone, SICER (version 1.1)  reference genome (human hg18) using the program SOAP (version 2.21) . Sequencion 1.1) , was useBinding sites to gene feature annotation: Enriched peaks were annotated to nearest gene (RefSeq genes) using Bioconductor package ChIPpeakAnno . DistribRegulatory regions, histone modification peaks, CpG and LADs abundance: Input-subtracted normalized average H1 variants read density in each enriched locations of regulatory regions, histone modification peaks, CpG and LADs were calculated, and representation in box-plot were made using in-house scripts. As a control, a random sample of genomic windows with equal width was used to perform the significance test (Kolmogorov–Smirnov test).http://genome.ucsc.edu/cgi-bin/hgLiftOver).Publicly available genome-wide location data analysis: Public ChIP-seq data, which includes H3K4me1, H3K4me2, H3K4me3, H3K27me3, H3K27ac, H3K9me3, H3K9ac, H3K36me3, P300, CTCF, FAIRE and DNase enriched genomic locations, are taken from ENCODE project. CpG island genomic location information (hg18) and the coordinates of LADs  were takOverlap analysis: Overlap of genomic position range data was done using BedTools . OverlapAverage ChIP signal profile: For sequencing data, ChIP signal around center of each given genomic location were calculated by using normalized input subtracted-average tags number in each 50 bp bins in a set window. Relative distance of each tag from above-mentioned position and average signal was determined by using ‘Sitepro’ script of CEAS package  and plotOccupancy of H1 variants at individual chromosomes: Occupancy of H1 variants at all human chromosomes is an average of the input-subtracted ChIP-seq signal in 50 bp windows. Heat map and dendrogram were done with in-house R scripts. Correlation between the occupancy of H1 variants  and gene expression and gene richness coefficient was done with in-house R scripts. Gene expression for each chromosome was computed as the average of the expression of all the available expressed genes. The gene-richness coefficient (GRC) for each chromosome was calculated as the ratio between the percentage of total genes present in each chromosome and the percentage of base pairs of each chromosome to the total human genome.in vitro transcribed into cRNA in the presence of Cy3-CTP using the Low input quick Amp kit (Agilent). Labeled samples were purified using RNeasy mini spin columns (Qiagen). Then, 600 ng of cRNA were preblocked and fragmented in Agilent fragmentation buffer and mixed with Agilent GEx Hybridization mix. Hybridization mix was laid onto each sector of subarray gasket slide and sandwiched against an 8 × 65K format oligonucleotide microarray  inside a hybridization chamber, which was hybridized overnight at 65°C. Subsequently array chambers were disassembled submerged in Agilent Gene Expression Buffer 1 and washed 1 min in another dish with the same solution with a magnetic stirrer at 200 rpm at room temperature, followed by 1 min in Agilent Gene Expression Buffer 2 with a magnetic stirrer at 200 rpm at 37°C and immediate withdrawal from the solution and air drying. Fluorescent signal was captured into TIF images with an Agilent scanner using recommended settings with Scan Control software (Agilent). Signal intensities were extracted into a tabulated text file using Feature Extraction software (Agilent) using the appropriate array configuration and annotation files. The normalized log2 intensities were obtained using quantile method with normalized expression background correction the Bioconductor Limma package in R.Total RNA was extracted using High Pure RNA isolation Kit (Roche) according to the manufacturer’s instructions. cDNA was obtained from 100 ng of total RNA using SuperScript VILO cDNA synthesis Kit (Invitrogen). High RNA integrity was assessed by Bioanalyzer nano 6000 assay. For each sample, 100 ng of total were reverse transcribed into cDNA with a T7 promoter and the cDNA was The correspondence of the human H1 variants nomenclature with its gene names is as follows: H1.0, HIF0; H1.1, HIST1H1A; H1.2, HIST1H1C; H1.3, HIST1H1D; H1.4, HIST1H1E; H1.5, HIST1H1B; H1X, HIFX.Supplementary Figure S1). In ChIP-qPCR experiments, an anti-HA antibody was used to specifically pull down H1-associated chromatin fragments in cells expressing H1-HAs . H1-associated chromatin included gene promoters, coding regions and repetitive DNA, irrespective of which H1-HA variant was immunoprecipitated . A few differences were observed between variants, e.g. there were relatively less H1.3 but more H1.4 and H1.5 at alphoid repeats.To determine whether the genomic distribution of human histone H1 differs between variants, we used ChIP combined with semiquantitative PCR (ChIP-qPCR), promoter array hybridization (ChIP-on-chip) and massive sequencing (ChIP-seq). Because there is a limited number of H1-variant–specific ChIP-grade antibodies (only H1.2 and H1X in our hands), we developed T47D-derived cell lines stably expressing HA-tagged versions of each of the five somatic H1 variants expressed in most cell types   . These cSupplementary Figure S4). Interestingly, the TSS-associated H1 valley was not observed at genes inactive in these cells, i.e. OCT4 and NANOG . Furthermore, under stimulating conditions H1 depletion at the TSS was increased at inducible promoters, such as steroid hormone responsive promoters (MMTV) or genes induced by mitogenic agents (JUN and FOS) . Noteworthily, in these early response genes, there was already an H1 valley in noninducing conditions and this became deeper on stimulation .The specificity of H1 variant distribution was investigated in more detail at gene promoters previously shown to contain H1 in distal regions located 10 kb upstream of their TSS and depletion of H1 at the TSS  . All thend NANOG C, while To explore the genome-wide distribution of the different H1 variants across gene promoters, we hybridized ChIP material obtained with variant-specific antibodies or corresponding to HA-tagged H1 variant-associated chromatin with a promoter tiling array containing probes for 30 893 transcripts (−3200 to +800 bp to the TSS) arising from 22 542 human promoters. The average log2 ratio of probe intensity for all transcripts was plotted against the relative distance to the TSS for each variant and an H1 valley close to the TSS was apparent in all cases. Interestingly, in the two H1.2 samples (endogenous H1.2 and H1.2-HA), the valley was more pronounced and slightly shifted toward the TSS, compared with that for the other H1 variants (endogenous H1X and H1.0/3/4/5-HA) A.FigureSupplementary Figure S8), and heat maps representing binding intensity were constructed for each variant, ranking promoters from highest to lowest gene expression .Subsequently, this ChIP-chip data was combined with gene expression data for ca. 20 000 of the transcripts, obtained with the parental cell line in a human expression array (Agilent) .In addition to protein-coding genes, the promoter array contained 1145 noncoding transcripts, including structural RNAs and transcribed pseudogenes, that overall presented a low expression rate compared with the complete transcriptome. An H1 valley at the TSS was only apparent on the ChIP-chip heat maps for endogenous and HA-tagged H1.2, in agreement with our observation that an H1.2 valley occurs even at weakly expressed promoters (Supplementary Table S2).Noteworthily, H1.2 abundance at distal promoter regions (−3200 to −2000 bp from TSS) was inversely proportional to gene expression, being more abundant at repressed promoters C. This wSupplementary Figure S11). This indicates that there is a preferential binding of H1.2 in some promoters (mostly repressed genes) compared with the other variants, and vice versa, many promoters are devoid of H1.2 but contain other H1 variants.Moreover, H1.2 abundance at distal promoter regions was inversely correlated with H3, H1X and H1-HA abundance, while H1.2-HA showed an intermediate pattern . The largest overlaps were between low2/highX promoters (553 genes), mainly corresponding to expressed genes . Taken together, our data indicated that promoters having few H1.2 variants are loaded with large amounts of other variants, not only with exogenously expressed H1.0-HA but also endogenous H1X. Expression analysis of such groups of genes found that genes with few H1 variants at distal promoters are highly expressed, and vice versa, but also that H1.2 content is the strongest predictor of gene expression .Venn diagrams were drawn for the top 10% genes with high or low H1.2 and high or low H1X at the distal promoter to identify genes presenting high2/lowX and vice versa . HeLa cells showed results similar to T47D, i.e. H1.2/H1X ratios were higher in COL4A3 and CUGBP2 genes than TMEM204 and TUBGCP5, although ratios in all genes were higher than in T47D reflecting a higher relative abundance of H1.2 in HeLa cells . On the other hand, H1.2/H1X ratios in MCF7 were similar in all four genes, due to higher H1X signals in COL4A3 and CUGBP2 genes. This result indicated that relative abundances between variants at promoters were not fully conserved between cell types, although the patterns in T47D and HeLa were similar. In relation to this, ChIP-chip of H1.2 and H1X in HeLa confirmed that these two variants do not coexist at exactly the same distal promoters .The universality of the relative H1.2/H1X abundance at representative genes was tested in two additional cell lines by ChIP-qPCR . The observed clustered distribution was well conserved between cell lines, but differed between H1 variants. H1X and H1.0-HA abundances were not clustered with the same pattern as gene expression. Rather, these variants were abundant at promoters located on gene-rich chromosomes 17 and 19, and depleted on the gene-poor chromosome 13 . In summary, H1.2 content at promoters is the best H1 reporter of gene expression.Next, we plotted heat maps of H1.2 abundance at the promoters of genes ranked according to their position along several human chromosomes A. IntereSupplementary Table S1). To confirm the results obtained by ChIP-chip, we focused first on the input-subtracted normalized average ChIP signal obtained around coding regions of genes grouped according to basal expression as before  of up to 50 million reads per sample . When we calculated the input-subtracted coverage of H1 variants across the peaks of selected core histone modifications, depletion of H1.0 and H1.2, and to some extent of H1.4 but not H1X, was associated with positive histone marks linked to strong enhancers such as H3K4me1, H3K4me2 and H3K27ac . H1 abundance at H3K4me3 and H3K9ac sites, enriched at TSS of active promoters, differed between variants, reflecting H1.2 depletion at the TSS of most genes but local enrichment of the other variants immediately after the TSS. No strong enrichment of H1 was found at negative histone marks such as H3K9me3 or H3K27me3. It is also worth noting that H1.2 abundance was lower at active marks than at those related with repression and chromatin compaction, in agreement with the observed correlation between H1.2 content and gene repression.In addition to the local displacement of H1 from active promoters, H1 variants were markedly depleted from other regulatory regions along the genome, namely, CCCTC-binding factor (CTCF) binding sites corresponding to insulators, and p300 binding sites associated with enhancers, but little affected at DNase hypersensitivity sites and FAIRE-identified regions representing open chromatin . When the input-subtracted coverage of H1 variants across LADs was calculated, H1.2 was the only variant showing enrichment . Interestingly, the H1.2 pattern was the most different from the other variants, endogenous H1X and HA-tagged variants showing patterns that were similar to each other and to that of H3, while the pattern for HA-tagged H1.2 was more similar to endogenous H1.2 than to other HA-tagged H1s. It is worth noting that long genome patches of low GC content were found to be devoid of all H1 variants except H1.2, which was enriched. We next performed genome-wide correlation analysis between the input-subtracted H1 variant signal and GC content. Low CG content was associated with high occupancy of H1.2 but low occupancy of the other variants, including H1X, and vice versa .We then examined individual chromosomes for the presence of the input-subtracted signal of the different H1 variants. Abundance of H1 was heterogeneous along chromosomes, showing extensive patches of enrichment or depletion of H1 compared with the input . Notably, H1 variants were clustered differently depending on whether they were replication-independent (H1.0 and H1X) or synthesized over the course of DNA replication only . Further, H1.0 and H1X had a more heterogeneous distribution between chromosomes (data not shown).Further comparison of the overall abundance of H1 variants at each individual chromosome revealed unique patterns creating corresponding clusters of chromosomes and H1 variants . InteresSupplementary Table S3). Most H1-enriched regions were inside genes (arbitrarily defined as from −5 kb upstream to +3 kb downstream of the TTS), whereas H1.2 peaks were more abundant at intergenic regions . On the other hand, all H1-depleted regions were more abundant inside genes, especially for H1.2. Within genes, H1.2-enriched regions were disfavored at promoters (−5 kb to +1 kb flanking TSS) compared with other H1 peaks, whereas H1.2-depleted regions were strongly favored, in agreement with ChIP-chip data presented in Supplementary Figure S20). Next, we analyzed the overlap between H1-enriched and depleted regions with CpG islands. CpG islands were enriched at H1.2-depleted regions and at regions enriched for the other variants, confirming the inverse correlation between CpG islands and H1.2 described above . As expected, regions overlapping with CpG sites were preferentially located at promoters. For example, 42% of H1.0- or H1X-enriched regions located at promoters overlapped with a CpG island, while this was the case for only 4–8% of regions enriched in these variants located at intergenic regions.Next, we searched specific regions of the genome either enriched or depleted for each H1 variant signal over input DNA with a fold change ≥2 using SICER software (Supplementary Table S3). Overlap analysis disclosed the number of genes containing peaks of a single variant or several variants , and expression analysis revealed that genes with only H1.2 peaks were less expressed than target genes containing peaks of any other H1 variant (Supplementary Table S3). On the other hand, genes presenting H1.2-depleted regions were highly expressed, while genes with depleted regions of H1.0, H1.4 or H1X were expressed at lower levels than the total transcriptome average . Except for those for H1.2, H1 peaks were as abundant in introns as in distal intergenic regions. On the other hand, depleted regions were similarly distributed across compartments in the different H1 variants, except H1.2-depleted regions, which were more abundant at promoters and less so at intergenic regions.We further investigated whether the identified H1-enriched regions fell within genes, proximal regulatory regions or distal intergenic regions using CEAS software . Again, In summary, our data shows that histone H1 is not uniformly distributed along the genome and there are differences between variants, H1.2 being the one showing the most specific pattern and strongest correlation with low gene expression in breast cancer cells.Herein, we have investigated the distribution of all somatic histone H1 variants present in breast cancer cells, i.e. H1.0, H1X and H1.2 to H1.5 by combining ChIP with genomic technologies such as tiling promoter array hybridization and high-resolution sequencing. After testing several H1 variant-specific antibodies that we and others have produced, only H1.2 and H1X commercial antibodies were found to be useful in the ChIP-qPCR experiments, and variant specific, as shown by performing ChIP experiments in H1.2 and H1X knockdown (KD) cells. Consequently, we generated stable cell lines expressing HA-tagged versions of the H1 variants at protein levels close to or below endogenous levels, despite mRNA levels of exogenous H1 forms being higher (data not shown). This suggests that H1 is tightly posttranscriptionally regulated to control the overall levels of H1 and the proportion between variants, which vary considerably across cell types and cell lines. HA-tagging allowed us to perform ChIP of all variants with the same antibody, ruling out the variability being due to diverse antibody specificity or affinity. We found that all the H1 variants studied are widely distributed along the genome and within promoters with few differences between HA-tagged H1.0, H1.3, H1.4 and H1.5. In contrast, endogenous H1.2 presents striking differences. We rule out the possibility that the differential distribution is due to antibody usage or protein overexpression, as endogenous H1X presented an occurrence similar to HA-tagged variants and exogenous H1.2-HA resembled its endogenous counterpart more closely than the other H1-HAs.On this basis, we report that, in the cell line investigated, H1.2 presents a variant-specific distribution and may have differential functions. In fact, we reported elsewhere that H1.2 KD produces unique effects, namely, cell cycle arrest at G1 and decreased nucleosome spacing, not seen in other H1 KDs, and these were observed not only in T47D cells but also in MCF7 cells . NonetheWe have noticed that H1.2-HA was not distributed in exactly the same way as endogenous H1.2 and showed intermediate features somewhat similar to the other H1-HAs. We believe that this recombinant protein has the H1.2 structural features that direct it to the natural H1.2-occupied sites, but owing to its overexpression it may also locate at distinct sites normally occupied by other H1 variants. We have observed, by ChIP, that on knock down of endogenous H1.2, H1.2-HA occupancy increased (data not shown), suggesting a relocation to H1.2 sites. Overall, we believe that caution should be taken when interpreting data generated with exogenous histone variants fused either to the Dam domain or to peptide tags.Our analysis has also shown that all H1s are removed from active promoters, with maximum depletion close to TSS but extending several nucleosomes upstream, beyond the reported NFR, and within the coding regions. These regions containing nucleosomes but not H1 may coincide with H2A.Z and H3.3-containing nucleosomes, as both H2A.Z and H3.3 have been reported to locate at active promoters surrounding the NFR, where they positively regulate transcription . AdditioInterestingly, we have found that immediate-early responsive promoters, under nonstimulating conditions, are prepared to respond to stimuli by keeping the TSS free of H1, indicating that mechanisms other than transcription initiation might dictate H1 clearance. In this case, there is also histone H3 depletion at the TSS compared with at the distal promoter in the absence of stimuli, indicating that the NFR might be maintained to allow rapid response after stimulation. Supporting our hypothesis, it has been recently proposed that transcription factors interact with DNA in a dynamic way, and some transcription factor–DNA interactions are established before the stimuli, especially at immediate-early genes .Comparison of H1 occupancy with H3 has shown that all H1s except H1.2 follow the distribution of the core histone, whether this represents nucleosome enrichment, stability or defined positioning through the cell population. Nonetheless, H1 depletion at promoters and regulatory sites (CTCF or p300 binding sites) is more extensive than H3, denoting that nucleosomes might be ejected from delimited sites such as the NFR at the TSS, but H1 might be depleted from larger regions encompassing several nucleosomes. This is in agreement with previous reports showing that dips of low H1 occupancy at TSS and regulatory sites are not due to a lack of nucleosomes as they show enrichment of the core histone variant H3.3 . MoreoveInitial ChIP-qPCR experiments indicated that all H1 variants were present at all tested promoters. Nonetheless, hybridization of ChIP material with a promoter array revealed that promoters might present differential H1 variant abundance . The mosMyc and H1dFLAG in ESCs, the closest orthologs of human H1.2 and H1.3, by Li et al. for human H1.5 in differentiated IMR90 fibroblasts, and by Izzo et al. for human Dam-H1.2 to H1.5 in IMR90 cells also  was more closely related to GC-rich sequences and LINES, and H1c (H1.2) to AT-rich sequences, Giemsa-positive regions and satellite DNA. It is conceivable that there are at least two groups of H1 variants with different distributions in each cell type, such that taken together histone H1 variants cover the whole genome, being present in most of the nucleosomes.The negative correlation observed between gene activity and H1.2 content found at promoters extended upstream toward the whole genomic region. Patches of H1.2 enrichment seem to be associated with gene repression, gene-poor regions , low GC content or LADs, features related to chromatin compaction . Moreovells also . HoweverWhether a single variant may present distinct features in different cell types rather than having intrinsic properties is an intriguing question. Factors involved may be the relative and absolute abundance of each variant and whether a genome needs more plasticity or is progressively silenced, i.e. pluripotency versus terminal differentiation. In this sense, Li et al. described the existence of zones of H1.5 enrichment in differentiated fibroblasts but not in ESCs , and it Cancer is another cellular state in which global chromatin rearrangement is observed. In fact, alterations in nuclear morphology are one of the characteristics of cancer cells. Tumor-originated cells accumulate genetic and/or epigenetic differences compared with nontumor cells, and chromatin is reorganized leading to altered gene expression programs and higher plasticity. The hallmark of cancer is dedifferentiation and gene dysregulation. DNA methylation and histone modifications are two epigenetic mechanisms that are altered in cancer cells. Moreover, large organized chromatin K (lysine) modifications are reduced in cancer , and genTumor cells are characterized by a different methylome from that of normal cells [reviewed in ]. There Similarly, within a long region of genomic sequence, genes are often characterized by having a higher GC content than the background GC content of the entire genome. We found that H1 variants except H1.2 are associated with higher GC content regions, consistent with the preferential location of H1-enriched regions within genes. H1.2 presents an inverse correlation with GC content at a genome-wide level and H1.2-enriched regions associate with lower GC content than other variants. In our analysis, H3 also associates preferentially with higher GC-content regions, in agreement with reports describing greater nucleosome-space occupancy coinciding with active transcription and higher GC contents .et al.  has been found to locate around the TSS of active genes . InsteadSeveral studies have compared the chromatin binding affinity and residence time on chromatin of the different H1 subtypes in different organisms or cell lines, as well as its nuclear localization, obtaining diverse, if not controversial, results on the functional heterogeneity of H1 variants. In general, H1.2 is among the variants presenting intermediate or low affinity for chromatin and, consequently, elevated mobility. Instead, H1.4 has been mostly associated with high affinity, low mobility and colocalization with heterochromatin ,101–103.Drosophila cells, five principal chromatin types have been described, H1 being present in all of them in different proportions  database under the accession number GSE49345.Supplementary Data are available at NAR Online.Ministerio de Ciencia e Innovación of Spain (MICINN) and FEDER [BFU2011-23057 to A.J.]; Ministerio de Economía y Competitividad [SAF2012-36199 to N.L.-B.]; Generalitat de Catalunya [2009-SGR-1222 to A.J.]; JAE-Doc contract from CSIC-MICINN (to J.-M.T.); TA contract from CSIC-MICINN (to R.M.); FPU predoctoral fellowship from MICINN (to L.M.-A.). Funding for open access charge: Ministerio de Ciencia e Innovación of Spain (MICINN) and FEDER [BFU2011-23057 to A.J.].Conflict of interest statement. None declared.


Pseudomonas putida BW11M1 produces a mixture of cyclic lipopeptide congeners, designated xantholysins. Properties of the major compound xantholysin A, shared with several other Pseudomonas lipopeptides, include antifungal activity and toxicity to Gram-positive bacteria, a supportive role in biofilm formation, and facilitation of surface colonization through swarming. Atypical is the lipopeptide’s capacity to inhibit some Gram-negative bacteria, including several xanthomonads. The lipotetradecadepsipeptides are assembled by XtlA, XtlB and XtlC, three co-linearly operating non-ribosomal peptide synthetases (NRPSs) displaying similarity in modular architecture with the entolysin-producing enzymes of the entomopathogenic Pseudomonas entomophila L48. A shifted serine-incorporating unit in the eight-module enzyme XtlB elongating the central peptide moiety not only generates an amino acid sequence differing at several equivalent positions from entolysin, but also directs xantholysin’s macrocyclization into an octacyclic structure, distinct from the pentacyclic closure in entolysin. Relaxed fatty acid specificity during lipoinitiation by XtlA (acylation with 3-hydroxydodec-5-enoate instead of 3-hydroxydecanoate) and for incorporation of the ultimate amino acid by XtlC  account for the production of the minor structural variants xantholysin C and B, respectively. Remarkably, the genetic backbones of the xantholysin and entolysin NRPS systems also bear pronounced phylogenetic similarity to those of the P. putida strains PCL1445 and RW10S2, albeit generating the seemingly structurally unrelated cyclic lipopeptides putisolvin (undecapeptide containing a cyclotetrapeptide) and WLIP (nonapeptide containing a cycloheptapeptide), respectively. This similarity includes the linked genes encoding the cognate LuxR-family regulator and tripartite export system components in addition to individual modules of the NRPS enzymes, and probably reflects a common evolutionary origin. Phylogenetic scrutiny of the modules used for selective amino acid activation by these synthetases indicates that bacteria such as pseudomonads recruit and reshuffle individual biosynthetic units and blocks thereof to engineer reorganized or novel NRPS assembly lines for diversified synthesis of lipopeptides.The rhizosphere isolate  Streptomyces and other actinomycetes are major producers of clinical antibiotics, several antimicrobials from other soil bacteria, such as Bacillus and Pseudomonas, contribute to their capacity to suppress fungal plant diseases Pseudomonas strains has been ascribed to in situ production of structurally diverse molecules: 2,4-diacetylphloroglucinol, phenazines, pyrrolnitrin, pyoluteorin, or lipopeptides Bacillus, Pseudomonas are prominent producers of lipopeptides with a range of different biological activities: antagonism of microbial competitors, protection against predators, facilitation of surface motility, biofilm formation, contribution to virulence of plant pathogens, triggering of the defense response in plants Certain genera of soil-dwelling and plant-associated bacteria, such as Streptomycetes, Myxobacteria, Bacilli, Pseudomonads, and Burkholderia, display a highly versatile secondary metabolism and, hence, have proven valuable sources for structurally very diverse metabolites with useful biological activities, including antibiotics. Whereas Pseudomonas strains can be assigned to specific groups, each named after a prototype compound: viscosin, amphisin, syringomycin, syringopeptin, or tolaasin Pseudomonas strains can produce variants of a particular lipopeptide by attaching a different fatty acid or by incorporation of a similar amino acid at a certain position due to relaxed substrate specificity of the biosynthetic enzymes. With the exception of syringafactins and its analogs, cichofactins Based on similarities in peptide length (ranging from 8 to 25 residues) and amino acid sequence, many of the lipopeptides produced by Pseudomonas biosynthetic genes for syringomycin, syringopeptin, syringafactin, arthrofactin, viscosin, orfamide, massetolide, putisolvin, entolysin, WLIP, and cichofactin have been described Pseudomonas lipopeptide systems are of Type A, obeying the “co-linearity rule”. This indicates that the order and number of the NRPS modules are co-linear to the amino acid sequence of the peptide product Pseudomonas lipopeptides with known stereochemistry, but the corresponding synthetases lack standalone epimerization (E) domains, as found in for instance Bacillus lipopeptide NRPSs Pseudomonas pyoverdine synthetases The Pseudomonas lipopeptides are harmful to fungi and oomycetes but their antibacterial activities are mostly confined to Gram-positive bacteria, while in general Gram-negative bacteria seem to be better protected by their different cell envelope architecture with a surface-exposed outer membrane Xanthomonas species are susceptible to the cyclic lipopeptide WLIP, a member of the viscosin group, produced by Pseudomonas putida RW10S2 Pseudomonas fluorescens LMG 5329 Pseudomonas aurantiaca PB-St2 Xanthomonas represents a major group of plant-associated bacteria, most of which cause plant diseases of economically important mono- and dicot crops Xanthomonas and Pseudomonas as metagenomic surveys have revealed that both genera of γ-proteobacteria constitute an important fraction of the microbial communities in the rhizosphere and phyllosphere of diverse plants Xanthomonas-antagonistic activity of Pseudomonas putida BW11M1, a strain isolated from banana rhizosphere in Sri Lanka, revealing the involvement of a new type of lipopeptide.Several Pseudomonas strains isolated from tropical crop roots P. putida BW11M1. Using an agar diffusion assay, spotted BW11M1 cells produced a growth inhibition halo with pathovars of different Xanthomonas species as indicator overlay . Furthermore, halo formation was not abolished by a non-specific protease spotted close to BW11M1 producer cells, pointing to a non-proteinaceous nature of the molecule(s) causing halo formation in the lawn of Xanthomonas cells (data not shown).Screening of a collection of  overlay . The groXanthomonas activity, a P. putida BW11M1 plasposon mutant library X. alfalfae subsp. alfalfae LMG 497 as indicator strain. Mutants lacking anti-LMG 497 activity were isolated and subjected to plasposon rescue Pseudomonas entomophila L48 encoding the enzymes EtlA, EtlB and EtlC that synthesize the cyclic lipopeptide entolysin etlR, the etlA-linked regulatory gene required for entolysin production recB and clpB mutants). The latter would be in line with the involvement of DnaK and ClpP in the production of the lipopeptides putisolvin by P. putidaP. fluorescensTo identify mutants lacking anti-P. putida BW11M1 apparently involved in biosynthesis of the substance inhibitory to Xanthomonas, tentatively designated xantholysin. In view of the anticipated large genomic DNA regions encoding multi-modular megasynthases, a fosmid library of genomic BW11M1 fragments was constructed. NRPS-specific PCR primers were designed based on the plasposon-flanking DNA sequences for the NRPS mutants listed in xtlA, xtlB and xtlC (acronym xtl referring to xanthomonad-lytic activity), in two unlinked DNA regions , adenylation (A) and thiolation (T) domain (P. entomophila biosynthetic system EtlA-EtlB-EtlC assembling the cyclic lipotetradecapeptide entolysin ) domain . A thioePseudomonas lipopeptide systems  which is similar to most known  strains  shows th strains  favors sxtlA, inactivated in mutant CMPG2201 is predicted to encode a LuxR-family protein  is not required for production of syringafactin viscBCR is present downstream of the xtlBC operon (data not shown), which is also the case for the wlpBC (WLIP) and etlBC (entolysin) operons The divergently transcribed gene upstream of  protein . Genes egulators .A. With pe level . A regulel syfR; , putisolxtlC (xtlD-xtlE) and xtlR (xtlF) potentially encode components of an export system for xantholysin , confirming that this is bacteriocin-mediated To further examine the antibacterial capacity of strain BW11M1 and the role played by xantholysin production in this, an expanded indicator panel composed of Gram-negative and Gram-positive bacteria  was testFBP 1430 . For theBacillus megaterium ATCC 13632, Bacillus subtilis LMG 7135 and Staphylococcus aureus ATCC 6358, and the actinomycetes Mycobacterium smegmatis DSM 43756, Rhodococcus erythropolis N11, Streptomyces coelicolor A3(2) and Streptomyces lividans TK24. The residual antagonistic activity towards these Gram-positive bacteria displayed by the xantholysin-deficient mutants again points to production of (an)other growth-inhibitory factor(s) by P. putida BW11M1 .Growth of most of the Gram-positive bacteria strains tested (seven out of nine) was inhibited by strain BW11M1: the firmicutes a BW11M1 . The anta BW11M1 . When tePseudomonas lipopeptides , no significant inhibition of Gram-negative bacteria was observed Arthrobacter strain (actinomycete) was susceptible to all tested compounds, except orfamide. Arthrofactin was also active against other actinomycetes .The inhibition of Gram-negative bacteria is a property not typically associated with lipopeptides, whereas Gram-positive bacteria are generally more susceptible P. putida BW11M1 and its xantholysin-deficient mutants to inhibit growth of several fungi was compared. Radial mycelial outgrowth was delayed or arrested for most of the fungi confronted with a colony of wild-type BW11M1 and this was connected to xantholysin production .To further assess the antimicrobial potential of xantholysin, the capacity of oduction . In addiP. tolaasii, and its analog sclerosin in vitro antifungal activity of entolysin has not been investigated, but production of entolysin is not involved in the biocontrol activity of P. entomophila L48 in a Pythium ultimum/cucumber setup Antifungal activity has been reported for several cyclic lipopeptides belonging to different structural groups P. putida BW11M1 also shows hemolytic activity, whereas mutants deficient in anti-Xanthomonas activity are devoid of it , compared to the strong surface translocation capacity of the wild-type strain (xtlR copy (pCMPG6204), was comparable to the wild-type behavior , 1761.2 Da , 1802.0 Da  and 1775.2 Da  , Fig. S71H-1H TOCSY spectrum of xantholysin A in DMF-d7  of the fatty acid chain.The 2D n DMF-d7  allowed spectrum . The TOCsonances . The ressonances  largely 3JCH correlation between the C-terminal Ile14 carbonyl and the Ser7 CH2β resonances in the HMBC spectrum. While spectral overlap prevented convincing observation of such correlation, indirect but clear evidence of the presence of the depsi bond is found in the chemical shift of the Ser7 CH2β protons, which is significantly higher (4.38 ppm and 4.58 ppm) compared to their random coil values (3.79 ppm and 3.95 ppm) β resonance does not experience such a strong downfield shift in comparison to other cyclic lipodepsipeptides that were assigned by NMR At this point, the only feature of the proposed xantholysin A structure which still remained to be confirmed was the depsi bond between Ile14 and Ser7. The predicted molecular mass of the above sequence when considering it as a linear lipopeptide deviates 18 Da with the experimental value, in agreement with the expected presence of the lactone bond. Based on previous experience in assigning cyclic lipodepsipeptides de novo analysis and full spectral assignment  and C86H148N18O23 (exact mass: 1801.0900 Da) for xantholysin B and C, respectively  and corpeptin B (3-hydroxydodec-5-enoic acid) Pseudomonas, promiscuity is observed with respect to chain length of the incorporated saturated 3-hydroxy fatty acids. Relaxed amino acid substrate specificity, as observed here for the terminal module in XtlC giving rise to minor amounts of xantholysin B, is common among Pseudomonas NRPS systems The modest quantities obtained for the minor xantholysin variants did not allow to record NMR data of sufficient quality for a signment . Neverthfference . The spefference , accountectively . Consideguration . This isPseudomonas sp. RtIB026. The main compound MA026 (PubChem CID 10285742) differs by two consecutive amino acids (Leu10-Gln11 in MA026 versus Gln10-Leu11 in xantholysin A). Congener R1MA026  contains an additional switch of two residues compared to xantholysin B . Congener R2MA026 differs from MA026 by a 3-hydroxydodec-5-enoyl instead of a 3-hydroxydecanoyl fatty acid moiety (same as the difference between xantholysins A and C). Given these striking similarities, it would be of interest to identify the biosynthetic genes of strain RtIB026 (patent strain FERM BP-7436) to compare the modular structure of its NRPSs with those of the xantholysin system. The MA026 structure suggests a peculiar A-domain switch between the last module of the second enzyme and the first module of the third enzyme in RtIB026, compared to XtlB and XtlC, respectively. Given the phylogenetic separation of the Val- and Leu-selective A-domains of module 9 and 14 in xantholysin , also affecting a number of xanthomonads. While xantholysin does not exert a growth-inhibitory effect on fellow pseudomonads, P. putida BW11M1 also produces a plant lectin-like bacteriocin to target other pseudomonads, including members of the P. syringae group P. syringae pathovars P. putida antibiotic promysalin, targeting other pseudomonads Erwinia amylovoraThe identification of xantholysin adds to the growing list of cyclic lipopeptides produced by pseudomonads. Like several other P. putida relative P. entomophila L48 Pseudomonas lipopeptide classification, based on amino acid sequence (length and similarity) and presence/type of macrocycle The genetic backbone of the xantholysin NRPS system bears considerable similarity to the one for entolysin biosynthesis by the P. putida strains generating lipopeptides that – at first glance – show little structural similarity: putisolvin  in viscosin-group lipopeptides cluster separately from the P. putida ones Phylogenetic comparison of the respective NRPS domains, the linked LuxR-family regulator and the associated tripartite export system consistently points to evolutionary relatedness of the components of the xantholysin and entolysin systems with those of Pseudomonas and Bacillus.Collectively, these observations suggest that these pseudomonads probably have recruited and reshuffled gene modules to engineer novel NRPS assembly lines for synthesis of new structural lipopeptide variants. In combination with rapidly accumulating genomic sequence data, high-throughput exploration of this part of the “parvome” Pseudomonas and Xanthomonas strains at 30°C and for Klebsiella pneumoniae ATCC 13883 and Staphylococcus aureus ATCC 6358 at 37°C. Aeromonas hydrophila ATCC 7966, Agrobacterium tumefaciens A208, Azospirillum brasilense Sp7, Burkholderia vietnamiensis LMG 10927, Mycobacterium smegmatis DSM 43756, Rhodococcus erythropolis N11, Serratia entomophila DSM 12358, Sphingomonas wittichii RW1, Variovorax paradoxus LMG 1797 and Yersinia enterocolitica LMG 7899 were grown at 30°C, and Bordetella avium 197N, E. coli and Salmonella enteritidis ATCC 13076 at 37°C, in LB . Nutrient broth (8 g/L) was prepared for growing Bacillus megaterium ATCC 13632 and Erwinia amylovora CFBP 1430 (at 30°C), and for Citrobacter freundii ATCC 8090, Enterobacter aerogenes ATCC 13048, Proteus vulgaris LMM 2011 and Shigella flexneri LMG 10472 (at 37°C). YEP  was used for Burkholderia cepacia LMG 1222, TY  for Bacillus subtilis LMG 7135 , and MRS (Difco lactobacilli MRS broth 55 g/L) for Lactobacillus plantarum LMG-P21295 (cultured at 30°C) and Lactobacillus rhamnosus GG . Streptomyces coelicolor A3(2) and Streptomyces lividans TK24 were cultivated in a medium composed of 10 g casitone, 5 g yeast extract and 5 g glucose per liter at 30°C. For solid media 15 g per liter agar was added. Antibiotics were added at the following concentration when required: kanamycin (50 µg/ml), ampicilin (100 µg/ml), tetracycline (20 µg/ml).Bacterial strains and plasmids used are described in P. putida BW11M1 was grown in 5 ml TSB for 8 h with shaking (200 rpm). Two µl of this culture (OD600 ∼1.8) was spotted onto a TSB agar and incubated overnight at 30°C. After exposure to chloroform vapor for 30 min to kill producer bacteria, the plates were opened in a laminar flow chamber to evaporate residual chloroform during another 30 min. Three ml of molten, semisolid agar (0.5%) was inoculated with 100 µl of a bacterial indicator cell culture (∼108–109 CFU/ml) and poured onto the plates as an overlay. Following day, plates (three replicates) were evaluated for growth inhibition halos in a turbid lawn of indicator cells. Protease sensitivity of the antimicrobial activity was verified by spotting 10 µl of proteinase K (20 mg/ml) near a chloroform-killed producer colony prior to overlay.Alternaria porri was grown on 6CA-TSB medium . 5 µl of overnight cell culture of P. putida BW11M1 and selected xantholysin-deficient mutants were spotted at a distance of ∼3 cm from the inoculum plug and incubated at 20°C for several days up to two weeks, depending on the growth rate of the fungi, before assessing the occurrence of mycelial growth inhibition zones. Indicator fungi are listed in An agar plug with fungal mycelium, grown for 1–2 weeks on half-strength PDA (potato dextrose agar) medium was placed at the center of an agar plate with appropriate medium at 20°C. PTA medium  plates were used for most fungi. Agaricus bisporus was carried out as described by Bessette Pseudomonas culture (∼108–109 CFU/ml) was spotted onto horizontally sliced pilei of mushroom basidiocarps (Agaricus bisporus). After absorption of the liquid by the sterile surface, mushrooms were incubated overnight at 30°C, sealed in a closed plastic box and saturated with water to prevent drying out. Following day, mushrooms were scored for the presence of browning. Cultures of wild type and mutants were tested in parallel .The effect of xantholysin production on Mod-OKm’ mutant library X. alfalfae subsp. alfalfae LMG 497 by the agar diffusion method. Each mutant from a 96-well microtiter plate was stamped onto TSB agar square petri dishes (12×12 cm) with a 96-prones replicator. Mutants lacking anti-LMG 497 activity were selected and confirmed twice. The plasposon-interrupted genes were identified by the plasmid rescue method Mod-OKm’-specific primers PGPRB-0293 (5′-TCTGGCTGGATGATGGGGCG-3′) and PGPRB-0294 (5′-CGGTTCCTGGCCTTTTGCTGGC -3′).A BW11M1 plasposon pTnP. putida BW11M1 genomic library in fosmid pCC2FOS, the CopyControl HTP Fosmid Library Production Kit protocol (Epicentre Biotechnologies) was applied. Based on the flanking sequences identified in the plasposon mutants, pairs of primers were designed to screen for fosmid clones containing the corresponding genomic DNA regions by colony PCR. Selected clones were compared by end-sequencing using pCC2FOS-specific primers PGPRB-1319 (5′-GTACAACGACACCTAGAC-3′) and PGPRB-1320 (5′-CAGGAAACAGCCTAGGAA-3′). Finally, three fosmids with DNA fragments covering the genomic regions of interest were sequenced at Macrogen (Korea). The insert size of the fosmids was estimated by separation of NotI-generated fragments using pulsed-field gel electrophoresis. A high copy number of the fosmids was induced by treating cells with the CopyControl Induction solution, prior to extraction of the fosmids with the FosmidMAX DNA purification kit (Epicentre Biotechnologies). The contigs with the regions containing the functionally characterized genes were submitted to GenBank (accession numbers KC297505 and KC297506).For construction of a Domains were identified using NRPS analysis tools xtlR gene was amplified using Platinum Pfx DNA polymerase (Invitrogen) with primers PGPRB-8013 (5′-TTGCTCTAGATCAGGTGCCGGCCATCCAGC-3′) and PGPRB-8014 (5′-CTCGGAATTCGGATCAAGGAAGACGACGAC-3′) and cloned into the pJB3Tc20 vector using the XbaI and EcoRI sites. The resulting construct (pCMPG6204) was transferred to E. coli DH5α. Conjugative transfer of pCMPG6204 to P. putida BW11M1 mutant CMPG2201 was achieved by triparental conjugation using E. coli HB101 bearing pRK2013 as helper strain. The phenotypes of a selected transconjugant were compared to the regulatory mutant.Complementation of mutant CMPG2201 was performed as previously described 600 ∼1.0 and then diluted 100-fold as initial culture . After 2 days of incubation at 30°C, biofilm formation was visualized by staining pegs with 0.1% crystal violet. Stained biofilms were subsequently extracted with 30% acetic acid and quantified by measuring absorbance of the solution at 570 nm. Hemolytic activity was assayed by spotting 2 µl of overnight-grown cells on TSB agar with 5% horse blood (Oxoid) plates and hemolysis halos were examined after incubating plates overnight at 30°C.Swarming ability was studied by spotting 2 µl of 8 h-grown cells on TSB medium solidified with 0.8% agar and evaluating surface spreading after incubation at 30°C for 16 to 24 h (three repeats for each sample). Biofilm formation was assayed according to Janssens et al. g, 30 min, 4°C), the supernatant was acidified by adding 9% HCl to lower the pH to pH 2–3. The precipitate formed was isolated by centrifugation  and washed twice with acidified distilled water (pH 3). Methanol was used to dissolve the pellet and the solution was kept at 4°C till further purification. After evaporation of solvent, the slurry was extracted with cold methyl tert-butyl ether to precipitate the peptide fraction. This procedure was repeated three times to obtain a crude peptide-rich mixture which was further purified by preparative RP-HPLC. Samples were dissolved in methanol (50 mg/ml) and eight injections of 1 ml were performed on a Phenomenex column (Luna C18(2) 250×21.2 mm, 5 µm particle size) operating at a flow rate of 17.5 ml/min. The ratio of the mobile phase solvents, 5 mM ammonium acetate in water and acetonitrile, was changed in a linear fashion from 50∶50 to 10∶90 over a time span of 15 minutes. The major compound (xantholysin A) was collected based on UV detection at λ = 214 nm. Two additional minor lipopeptides, shown to be xantholysin variants B and C, were isolated by analytical HPLC using an Agilent 1100 series instrument equipped with a Phenomenex column (Luna C18(2), 250×4.6 mm, 5 µm particle size) and operating at a flow rate of 0.8 ml/min. The ratio of mobile phase solvents, 5 mM ammonium acetate in water and acetonitrile, was changed from 35∶65 to 25∶75 over a time span of 15 minutes. To identify bioactive fractions, samples from collected fractions were spotted on a TSB agar plate and overlayed with indicator cells after evaporation of the solvent (with non-polar phase solvent as negative control).Overnight TSB-grown BW11M1 cell culture was used to inoculate fresh TSB medium at a volume ratio of 1∶100 and incubated at 30°C for at least 2 days with shaking (200 rpm). After removing cells through centrifugation . Samples were infused at 3 µl/min and spectra were obtained in positive ionization mode with a resolution of 15000 FWHM and accuracy of 0.5 ppm RSD using leucine enkephalin as lock mass. Additional LC-MS data were collected on the extracted mixture prior to purification with an Agilent 1100 Series HPLC with an ESI detector type VL, equipped with a Phenomenex column (Luna C18(2), 250×4.60 mm, 5 µm particle size). The flow rate was 1 ml/min. The mobile phase solvents, 5 mM ammonium acetate in water and acetonitrile, were linearly changed from a 25∶75 ratio to a 0∶100 ratio over a time span of 15 minutes.d7 (Eurisotop). High quality HP-7 (New Era Ent. Inc) NMR tubes were used. NMR experiments were performed on a Bruker Avance III spectrometer operating at 500.13 MHz and 125.76 MHz for 1H and 13C, respectively, and equipped with a 5 mm 1H BBI-Z probe. Due to the low absolute quantities of compound after purification, the xantholysin variants were dissolved in 10 µl DMF-d7 for measurements using 1 mm capillaries. In this case, NMR experiments were performed on a Bruker Avance II spectrometer operating at 700.13 MHz and 176.04 MHz for 1H and 13C, respectively, and equipped with a 1 mm 1H, 13C, 15N TXI-Z probe. For both analysis of xantholysin A and its variants, sample temperature was set to 55°C throughout, as significant line broadening effects occurred at lower temperatures. 2D spectra measured for structure elucidation include a 1H-1H TOCSY with a 90 ms MLEV-17 spinlock, a sensitivity-improved, multiplicity edited, 1H-13C gHSQC applying adiabatic 180° pulses, a 1H -1H NOESY with a 300 ms mixing time and a 1H-13C gHMBC experiment optimized for a carbon-proton coupling of 8 Hz. Standard pulse sequences as present in the Bruker library were used throughout. Typically, 2048 data points were sampled in the direct dimension for 256 data points in the indirect one, with the spectral width respectively set to 12 ppm along the 1H dimension and 110 ppm (gHSQC) or 220 ppm (gHMBC) along the 13C dimension. For 2D processing, the spectra were zero filled to obtain a 2048×2048 real data matrix. Before Fourier transformation, all spectra were multiplied with a squared cosine bell function in both dimensions except for the gHMBC where a squared sine bell was applied.High-resolution mass spectra were recorded on an Agilent 6220A time-of-flight mass spectrometer, equipped with an Agilent ESI/APCI multimode source. The ionization mode was set to APCI , while the mass spectra were acquired in 4 GHz high-resolution mode with a mass range set to 3200 Da. All NMR measurements on xantholysin A were performed on a sample of 6.5 mg dissolved in 600 µl DMF-Figure S1Cladogram representation of a maximum-likelihoodtree inferred from amino acid sequence alignment of condensation domains extracted from characterized Pseudomonas NRPSs. The lipopeptide-specific codes are specified in (PDF)Click here for additional data file.Figure S2Maximum-likelihoodtree of thioesterase domains of characterized LP-producing Pseudomonas NRPSs. The clusters with tandemly organized domains TE1 (red) and TE2 (green) are shown in different colors. Lipopeptide-specific codes as in Lysobacter sp. ATCC 53042 and the mono-TE domain of syringomycin synthetase SyrE from P. syringae pv. syringae B301D are included for comparison. The internal residue involved in cyclization with the carboxyterminal amino acid is specified for each TE1/TE domain . The scale bar represents 0.5 substitutions per site.(PDF)Click here for additional data file.Figure S3Comparison of cognate regulators and associated export systems in lipopeptide-synthesizing Pseudomonas. Maximum-likelihood trees inferred from amino acid sequence alignments of (A) LuxR-family regulators encoded by genes linked with the respective initiatory NRPS genes and (B) the components of tripartite MacA/MacB/OprM-like export systems ). Lipopeptide-specific codes as in syrE. In panel B, the Syf and Arf systems are not included (no sequences available for the corresponding OprM-like protein). The scale bars represent 0.09 (panel A) and 0.04 (panel B) substitutions per site. The xantholysin cluster (blue) and viscosin cluster (green) are shown in different colors.(PDF)Click here for additional data file.Figure S4Growth inhibition of representative indicator bacteria by purified xantholysin. 10 µl-samples of purified xantholysin in methanol, containing 18 µg (A) or 9 µg (B) were spotted on an agar plate and overlaid with indicator cells after solvent evaporation. Methanol control spots did not cause growth inhibition.(PDF)Click here for additional data file.Figure S5Antifungal activity of xantholysin. Growth inhibition of fungi by P. putida BW11M1 (WT) and xantholysin-deficient mutants . The application pattern of bacterial cell suspensions spotted around a centrally positioned plug with fungal mycelium is shown schematically in (A). (B) Alternaria longipes CBS 620.83, (C) Ascochyta pisi MUCL30164, (D) Botrytis cinerea MUCL30158, (E) Colletotrichum gloeosporoides SR24, (F) Fusarium culmorum MUCL30162, (G) Fusarium graminearum MUCL30161, (H) Fusarium oxysporum MUCL909, (I) Fusarium oxysporum MUCL30160, (J) Fusarium oxysporum f. sp. radices-lycopersi CBS 873.95, (K) Fusarium oxysporum f. sp. vasinfectum CBS 410.90, (L) Gloeosporium musarum MUCL500, (M) Gloesporium solani CBS 194.32, (N) Nectria haematococca MUCL20259, (O) Pyrenophora tritici-repentis MUCL30217, (P) Rhizoctonia solani CBS 211.84.(PDF)Click here for additional data file.Figure S6Chromatographic separation of xantholysin congeners. LC-MS chromatogram of the extracted mixture prior to purification using UV-detection at 214 nm.(PDF)Click here for additional data file.Figure S7Mass spectrometry of xantholysin congeners. Mass spectra of xantholysin A and its variants obtained during LC-MS analysis of the extracted mixture prior to purification. Preliminary experiments with a high-resolution instrument showed that the peaks represent ions with charge z = 2.(PDF)Click here for additional data file.Figure S81D NMR analysis of xantholysin A. 1D 1H spectrum of xantholysin A in DMF-d7 solution, 55°C, 500 MHz.(PDF)Click here for additional data file.Figure S92D NMR analysis of xantholysin A. 2D 1H-1H TOCSY spectrum of xantholysin A in DMF-d7 solution, 55°C, 500 MHz, revealing the characteristic amino acid spin system patterns.(PDF)Click here for additional data file.Figure S10Nuclear Overhauser effect spectroscopy of xantholysin A. Established NOE contacts in xantholysin A, observed in a 2D 1H-1H NOESY spectrum with 300 ms mixing time.(PDF)Click here for additional data file.Figure S11High resolution mass spectrum of xantholysin A. (A) Full mass spectrum. (B) Zoom on the [M+H]+ molecular ion peaks. Expected exact mass of xantholysin A (C84H146N18O23)+H+: 1776.0881 Da; observed exact mass of xantholysin A+H+: 1776.0837 Da.(PDF)Click here for additional data file.Figure S121D NMR analysis of xantholysin B. 1D 1H spectrum of xantholysin variant 1, in DMF-d7 solution, 55°C, 700 MHz.(PDF)Click here for additional data file.Figure S131D NMR analysis of xantholysin C. 1D 1H spectrum of xantholysin variant 2, in DMF-d7 solution, 55°C, 700 MHz. The inset shows the signals arising from the alkene protons of the 3-hydroxydodec-5-enoic acid moiety, on top of an unidentified resonance from an impurity.(PDF)Click here for additional data file.Figure S142D NMR analysis of xantholysin B. 2D 1H-1H TOCSY spectrum of xantholysin variant 1, in DMF-d7 solution, 55°C, 700 MHz, revealing the characteristic amino acid spin system patterns.(PDF)Click here for additional data file.Figure S15High resolution mass spectrum of xantholysin B. (A) Full mass spectrum. (B) Zoom on the [M+H]+ and [M+Na]+ molecular ion peaks. Expected exact mass of xantholysin B (C83H144N18O23)+H+: 1762.0724 Da; observed exact mass of xantholysin B+H+: 1762.0647 Da.(PDF)Click here for additional data file.Figure S16High resolution mass spectrum of xantholysin C. (A) Full mass spectrum. (B) Zoom on the [M+H]+ and [M+Na]+ molecular ion peaks. Expected exact mass of xantholysin C (C86H148N18O23)+H+: 1802.1037 Da; observed exact mass of xantholysin C+H+: 1802.0973 Da.(PDF)Click here for additional data file.Figure S17NMR analysis of fatty acid moiety in xantholysin C.1H and 13C chemical shift comparison between the lipid tail of xantholysin A and variant 2. (A) Experimental 1H (red) and 13C (blue) chemical shifts of the xantholysin 3-hydroxydecanoic acid moiety, compared to predicted 13C chemical shifts (green). (B) Experimental 1H (red) and 13C (blue) chemical shifts of the xantholysin variant 2 3-hydroxydodec-5-enoic acid moiety, compared to predicted 13C chemical shifts (green) assuming a cis-configuration. (C) Predicted 13C (green) chemical shifts of the xantholysin variant 2 3-hydroxydodec-5-enoic acid moiety assuming a trans-configuration. 13C chemical shift predictions were calculated using ChemNMR Pro 12.0 as implemented in the ChemDraw Ultra 12.0 software . In the case of cis-3-hydroxydodec-5-enoic acid, the predicted 13C chemical shifts indicate a decrease in both the γ and ζ 13C chemical shifts compared to the HDA moiety (36.8 ppm→33.1 ppm and 29.3 ppm→27.7 ppm respectively). In the case of the trans-3-hydroxydodec-5-enoic acid, an increase in these same chemical shifts is predicted (36.8 ppm→39.1 ppm and 29.3 ppm→33.7 ppm respectively). In the cis configuration, the van der Waals radii of the hydrogens of the two carbons flanking the double bond are overlapping due to their spatial proximity, as opposed to the trans configuration. This steric compression causes an additional shielding and thus upfield shift of the associated carbons, which is not present in the case of the trans configuration  Carbon-13 NMR Spectroscopy: High-Resolution Methods and Applications in Organic Chemistry and Biochemistry, 3rd edition. Weinheim: VCH Verlagsgesellschaft mbH. 515 p.). The experimental values of the 3-hydroxydodec-5-enoic acid moiety compared to those of the HDA moiety (37.91 ppm→35.53 ppm and 29.60 ppm→27.28 ppm for the γ and ζ 13C nuclei respectively) show that the 13C chemical shifts correspond significantly better to the case of the cis-configuration, indeed showing a decrease. Therefore, this provides a significant indication for the lipid tail in xantholysin variant 2 to be in the cis-configuration.(PDF)Click here for additional data file.Table S1Characterization of antibacterial activity of P. putida BW11M1. Homology of genes disrupted in BW11M1 plasposon mutants lacking antibacterial activity using X. alfalfae subsp. alfalfae LMG 497 as indicator strain.(PDF)Click here for additional data file.Table S2In silico analysis of adenylation domains in xantholysin synthetases. Predicted substrate specificity of the A domains in the xantholysin NRPSs.(PDF)Click here for additional data file.Table S3Antagonistic activity spectrum of P. putida BW11M1 wild type (WT) and xantholysin-deficient mutants. The indicators shown are listed in Xanthomonas strains a larger turbid halo was observed around a smaller clear halo. Additional italicized values in parentheses refer to the presence of a ‘secondary’ turbid growth inhibition halo.(PDF)Click here for additional data file.Table S4Analysis of bacterial susceptibility to P. putida BW11M1. List of non-Xanthomonas bacteria used as indicators.(PDF)Click here for additional data file.Table S5Antifungal activity of P. putida BW11M1 and xantholysin-deficient mutants. The effect on mycelial growth near a bacterial colony is indicated: (+) inhibition by wild type; (↓) or (−), reduced or no inhibition by xtl mutants compared to WT (as observed on PTA medium). For a particular indicator, the same phenotype was observed for the xtlA, xtlB, xtlC and xtlR mutants , collectively designated xtl mutants. The inhibitory patterns for selected fungal strains are shown in (PDF)Click here for additional data file.Table S6NMR analysis of xantholysin A.1H and 13C NMR assignment of xantholysin A in DMF-d7 solution, 55°C.(PDF)Click here for additional data file.


S100A9 was originally discovered as a factor secreted by inflammatory cells. Recently, S100A9 was found to be associated with several human malignancies. The purpose of this study is to investigate S100A9 expression in gastric cancer and explore its role in cancer progression.S100A9 expression in gastric tissue samples from 177 gastric cancer patients was assessed by immunohistochemistry. The expression of its dimerization partner S100A8 and the S100A8/A9 heterodimer were also assessed by the same method. The effect of exogenous S100A9 on motility of gastric cancer cells AGS and BGC-823 was then investigated.P = 0.009) and tumor invasion (P = 0.011). S100A9 was identified as an independent prognostic predictor of overall survival of patients with gastric cancer (P = 0.04). Patients with high S100A9 cell count were with favorable prognosis (P = 0.021). Further investigation found that S100A8 distribution in human gastric cancer tissues was similar to S100A9. However, the number of S100A8-positive cells did not positively correlate with patient survival. The inflammatory cells infiltrating cancer were S100A8/A9 negative, while those in gastritis were positive. Furthermore, exogenous S100A9 protein inhibited migration and invasion of gastric cancer cells.S100A9 was specifically expressed by inflammatory cells such as macrophages and neutrophils in human gastric cancer and gastritis tissues. Statistical analysis showed that a high S100A9 cell count (> = 200) per 200x magnification microscopic field in cancer tissues was predictive of early stage gastric cancer. High S100A9-positive cell count was negatively correlated with lymph node metastasis (Our results suggested S100A9-positive inflammatory cells in gastric cancer tissues are associated with early stage of gastric cancer and good prognosis. Gastric cancer is one of leading causes of cancer mortality worldwide. A total of 989,600 new stomach cancer cases and 738,000 deaths were estimated to have occurred in 2008, and over 70% of new cases and deaths occur in developing countries such as China . Gastric2+-binding domains. After calcium binding, S100A9 interacts with another S100 family member S100A8 to form the functional heterodimer called calprotectin [Members of the S100 family of proteins are emerging as biomarkers in multiple types of tumors . The S10rotectin . S100A9,rotectin . S100A9 rotectin , prostatrotectin , and brerotectin ,19, whilrotectin . In colorotectin . In addirotectin . In gastrotectin ,24. HoweIn this study, we used gene expression analysis to compare S100A9 expression in gastric cancer tissues and in the adjacent, ostensibly normal tissues. Immunohistochemical staining revealed S100A9 in tumor-associated inflammatory cells. Furthermore, we addressed the correlation between the number of S100A9-positive cells in tumor tissues and the clinicopathological features. We also addressed the co-localization of S100A9 and S100A8 as well as the localization of the dimer calprotectin by immunofluorescence. Finally, to gain insight into the function of S100A9 in cancer cells, we investigated the effect of the recombinant S100A9 protein on migration and invasion of gastric cancer cells AGS and BGC-823.This investigation was performed after approval by Ethics Committee of Peking University Cancer Hospital. Informed consent was obtained from each patient. One hundred seventy-six patients with gastric cancer were studied. 124 males and 53 females  were diagnosed and surgically treated in Peking University Cancer Hospital between 1998 and 2004. The depth of tumor invasion, histological grade, lymph node metastasis, liver metastasis, and vascular invasion were obtained from clinical and histopathological reports. Stage of gastric cancer was classified according to the 7th edition tumor-node metastasis (TNM) classification recommended by the American Joint Committee on Cancer. None of the patients received chemotherapy or radiation therapy preoperatively. All patients were followed up until January 2010. After gastrectomy, one part of resected specimen was fixed in 10% formalin and processed routinely for pathological assessment, and another was snap-frozen in liquid nitrogen stored at −80°C for RNA extraction. In addition, 30 matched metastatic lymph nodes were also collected from these patients. Ten cases of chronic appendicitis tissues with exacerbation were provided by the Department of General Surgery, the affiliated hospital of Qingdao University Medical College.Four-micrometer sections from formalin-fixed paraffin-embedded tissues were mounted on poly-L-lysine-coated slides and then deparaffinized in xylene and rehydrated through alcohol to distilled water. Endogenous peroxidase activity was blocked with 3% hydrogen peroxide for 15 minutes at room temperature. After pressure cooking the slides in 10 mmol/L EDTA (pH 8.0) for 3 minutes, the sections were incubated with 5% goat serum, then incubated overnight at 4°C with mouse anti-S100A9 antibody , or mouse anti-S100A8 antibody , or mouse anti-S100A8/A9 antibody . Primary antibodies were detected using a two-step EnVision System . Horseradish peroxidase and diaminobenzedene hydrochloride (DAB) were enzyme and chromogen employed. Expression of S100A9, S100A8 and S100A8/A9 were also detected in Cybrdi tissue microarray slides  containing chronic gastritis with metaplasia (57 cases) and gastric carcinoma tissues (23 cases). Ten cases of chronic appendicitis specimens with exacerbation were served as positive control for S100A8/A9.S100A9 and S100A8 were stained in the inflammatory cells such as macrophages and neutrophils infiltrating tumor tissues. Positive cells showed a variable degree of cytoplasmic staining. Images were acquired using Ariol image analysis system . The scanner is based on an Olympus BX61 microscope with a motorized stage and autofocus capabilities equipped with a camera. Slides were scanned at 200× magnification. The degree of monoclonal S100A9 or S100A8 antibody reactivity in each tissue section was assessed by counting the number of stained inflammatory cells in three 200× magnification scopes. This was conducted by two independent pathologists with the help of an automatic microscope system and the image processing software  were incubated 1.5 hours at room temperature with mouse anti-S100A9 antibody (1:200) pre-labeled with the Zenon Alexa Fluor 647 Mouse IgG Labeling Kit , and either the anti-S100A8 antibody (1:200) or anti-S100A8/A9 antibody (1:200) pre-labeled with the Zenon Alexa Fluor 488 Mouse IgG Labeling Kit . Confocal images were acquired using the Leica TCS SP5 confocal microscope . In addition, the nuclei counterstained with DAPI , excitation at 358 nm.Specimens of chronic appendicitis tissues with exacerbation were incubated with anti-S100A9 antibody , and anti-S100A8/A9 antibody  as a positive control for the specific S100A8/A9 heterodimer expression.2 atmosphere.Both cell lines in this study were previously profiled by microarray analysis and were regularly verified using STR analysis (short tandem repeat DNA fingerprinting) . Gastric6 cells/mL (200μL/chamber). S100A9 recombinant protein was added to the upper chamber medium at 0, 10, 20, 50, or 100 ng/ml. The bottom chamber was filled with 500μL medium containing 10% FCS. Cells were allowed to migrate for 48 h at 37°C. Cells that remained in the upper chamber were removed with a cotton swab, and cells that had penetrated to the bottom side of the membrane were stained in Cell Stain Solution for 15 minutes, and counted in nine randomly selected microscopic fields (200×) per well. Each insert was then transferred to an empty well and incubated in 200μL of Extraction Solution. After 10 minutes, 100μL of solution from each sample were transferred to a 96-well microtiter plate and measured in a plate reader at OD560nm.CytoSelect 24-Well Cell Invasion Assay kit was purchased from Cell Biolabs, USA. S100A9 recombinant protein was purchased from BMA Biomedicals, Switzerland. Cell invasion assays were performed with Transwell Inserts, which allows cells to migrate through an 8 μm pore size polycarbonate membrane. The upper surface of the insert membrane was coated with a uniform layer of dried basement membrane matrix solution. Cells resuspended in serum-free medium were plated in the upper chamber of each Transwell at a density of 10Cell mobility was assessed using a wound healing assay. Cells were seeded into six-well tissue culture dishes and cultured until confluent to get a cell monolayer, which was then wounded using sterile 200 μl pipette tips. Any cellular debris was removed by washing with PBS. The wounded monolayer cell was then incubated in medium with 100 ng/ml S100A9 recombinant protein. Control cells were treated with serum-free RPMI-1640 medium. Time-lapse images were captured using an inverted phase-contrast microscope at 200× magnification for 0, 24, and 48 h. The cell migration ability was evaluated by calculating the average cell migration distance.χ2 test was performed. Cumulative survival was estimated with the Kaplan–Meier method, and comparisons between groups were done with a log-rank test. Overall survival was measured from date of initial surgery to date of death, counting death from any cause as the end point, or the last date of information as the end point if no event was documented. A multivariate analysis of the Cox proportional hazards regression model  was created to assess the influence of each variable on survival. Significance was set at P < 0.05.Clinicopathologic variables were extracted from clinical and histopathological reports. ROC curves were used in determining the cut-off value of the S100A9-positive inflammatory cell count in evaluating pathological TNM stage. The association of S100A9-positive inflammatory cell count with different TNM stages was done with the Wilcoxon rank-sum test. To obtain associations between S100A9 or S100A8 cell count and clinicopathologic variables, the data was cross-tabulated and a P = 0.00241, Figure In a previous gene array analysis, we found that gastric cancer tissues were distinguished from adjacent noncancerous mucosa by characteristic differences in their gene expression patterns . The divImmunohistochemistry of specimens from 177 gastric cancer patients showed that S100A9 was positive in all primary cancer tissues with immunostaining exclusively located in inflammatory cells such as macrophages and neutrophils infiltrating primary tumor tissues (The different cell types in tissue samples were identified by two independent pathologists) .To evaluate the extent of S100A9 expression in gastric cancer-associated environment, the number of S100A9-positive inflammatory cells in each tumor tissue was measured by averaging the cell counts of three fields  in the area with the greatest number of positive cells at the site of deepest tumor invasion. Correlation between cell count and clinicopathological parameters and patient survival was analyzed using Wilcoxon rank-sum test and Kaplan–Meier method. As shown in Figure P = 0.017, Figure Then we tested the prediction power of the S100A9 cell count for tumor stage in gastric cancer. Based on TNM stage, patients were divided into two groups, less advanced group (stage I + II) and advanced group (stage III + IV). Area under curve (AUC) obtained from the receiver operating characteristic (ROC) curves using the S100A9-positive inflammatory cells count was 0.623 for pathological TNM stages. The cutoff value was 198.5  per 200× magnification field with 64.3% sensitivity and 61.9% specificity for tumor stage prediction . Correlation between S100A9 cell count and other clinical features such as sex, age, tumor location, liver metastasis (M stage), vascular invasion and differentiation were not statistically significant  (Table P = 0.006), liver metastasis (P = 0.000), and S100A9 cell count (P = 0.046) to be independent factors in predicting overall survival (Table Low S100A9 cell count was found to be correlated with tumor invasion depth (T stage), lymph node metastasis (N stage), and clinical TNM stage . Invasive cells were counted in nine randomly selected microscopic fields (200×). Results showed that S100A9 recombinant protein slightly inhibited AGS cell invasion Figure A, while Human cancer is a chronic disease that originates from transformed cells harboring genetic as well as epigenetic alterations. However, cancer is not composed merely of cancer cells. Cancer tissue contains other cell types, including fibroblasts and epithelial cells, immune cells, and cells forming blood vessels and lymphatic vasculature . In thisS100A9, a member of S100 family, is abundant in granulocytes, monocytes and activated keratinocytes during various inflammatory conditions. In this study, we found that S100A9 was specifically located in inflammatory cells infiltrating gastric cancer tissues and chronic gastritis tissues, while all gastric cancer cells or adjacent cells of gastric mucosa did not express S100A9. Our results agree with previous studies demonstrating high expression of S100A9 in infiltrating immune cells in various cancer types including colorectal cancer  and pancCorrelation among S100A9 expression, clinicopathological features and patient prognosis varies in different cancer types. In lung cancer  and invaThe association of S100A9 expression with different clinicopathological features and patient prognosis among a variety of cancer types suggests that the function of this molecule can be diverse. Growing evidence suggests that S100A9 and its close partner S100A8 and the heterodimer of S100A8/A9 can exhibit both pro- and anti-tumorigenic functions during tumorigenesis ,37. On oThe inconsistent association of S100A expression with clinicopathological features and patient prognosis among cancers may be caused by the complexity of the cancer microenvironment. Immune mediators such as S100A9 can play both anti-tumor and tumor promoting roles depending on the cancer types ,40. StudS100A9 was specifically expressed in inflammatory cells infiltrating gastric cancer tissues and chronic gastritis tissues. Presence of S100A9-positive inflammatory cells in cancer tissues correlates with an early stage cancer and a better prognosis in patients with gastric cancer.The authors have declared that no competing interests exist.J-FJ and L-HZ conceived the design of the study and were in charge of its coordination. BF, X-YZ and Y-n J carried out the immunohistochemical assays. BF, L-HZ, X-HW and X-FX performed cell line assays. Y-QL, X-JC, HD, YH, Y-AL, WZ, A-PL and J-YL participated in the clinical materials collection. BF and L-HZ conducted statistical analysis. J-FJ, BF and L-HZ drafted the manuscript. Z-JN provided chronic appendicitis tissues with exacerbation. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/316/prepubFigure S1. To help count the inflammation cell in cancer tissues, the images under 200x magnification (A) were captured and processed using customized actions to automate pickup of immunostained cells (B) in Photoshop software (ver. 6.0). Then two pathologists counted the cells in the images (both A and B) independently.Click here for fileTable S1.  Association of S100A8-positive inflammatory cell count in cancer tissues with clinicopathological parameters in gastric cancer patients.Click here for fileFigure S2.  High S100A9, not S100A8 cell count indicates better outcome in gastric cancer patients. (A) Kaplan-Meier analysis of overall survival for high S100A8 cell count (> = 64) group and low S100A8 cell count (< 64) group in 125 gastric cancer patients. (B) Kaplan-Meier analysis of overall survival for high S100A9 cell count (> = 200) group and low S100A9 cell count (< 200) group in the same cohort of gastric cancer patients.Click here for file