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Hinxton, United Kingdom

Belda E.,University of Valencia | Moya A.,University of Valencia | Moya A.,CIBER ISCIII | Bentley S.,Sanger Institute | And 2 more authors.
BMC Genomics | Year: 2010

Background: Genome reduction is a common evolutionary process in symbiotic and pathogenic bacteria. This process has been extensively characterized in bacterial endosymbionts of insects, where primary mutualistic bacteria represent the most extreme cases of genome reduction consequence of a massive process of gene inactivation and loss during their evolution from free-living ancestors. Sodalis glossinidius, the secondary endosymbiont of tsetse flies, contains one of the few complete genomes of bacteria at the very beginning of the symbiotic association, allowing to evaluate the relative impact of mobile genetic element proliferation and gene inactivation over the structure and functional capabilities of this bacterial endosymbiont during the transition to a host dependent lifestyle.Results: A detailed characterization of mobile genetic elements and pseudogenes reveals a massive presence of different types of prophage elements together with five different families of IS elements that have proliferated across the genome of Sodalis glossinidius at different levels. In addition, a detailed survey of intergenic regions allowed the characterization of 1501 pseudogenes, a much higher number than the 972 pseudogenes described in the original annotation. Pseudogene structure reveals a minor impact of mobile genetic element proliferation in the process of gene inactivation, with most of pseudogenes originated by multiple frameshift mutations and premature stop codons. The comparison of metabolic profiles of Sodalis glossinidius and tsetse fly primary endosymbiont Wiglesworthia glossinidia based on their whole gene and pseudogene repertoires revealed a novel case of pathway inactivation, the arginine biosynthesis, in Sodalis glossinidius together with a possible case of metabolic complementation with Wigglesworthia glossinidia for thiamine biosynthesis.Conclusions: The complete re-analysis of the genome sequence of Sodalis glossinidius reveals novel insights in the evolutionary transition from a free-living ancestor to a host-dependent lifestyle, with a massive proliferation of mobile genetic elements mainly of phage origin although with minor impact in the process of gene inactivation that is taking place in this bacterial genome. The metabolic analysis of the whole endosymbiotic consortia of tsetse flies have revealed a possible phenomenon of metabolic complementation between primary and secondary endosymbionts that can contribute to explain the co-existence of both bacterial endosymbionts in the context of the tsetse host. © 2010 Belda et al; licensee BioMed Central Ltd. Source

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LONDON (Reuters) - Scientists say they have conclusive evidence that changes to a gene called SETD1A can dramatically raise the risk of developing schizophrenia - a finding that should help the search for new treatments. The team, led by researchers at Britain's Wellcome Trust Sanger Institute, said damaging changes to the gene happen very rarely but can increase the risk of schizophrenia 35-fold. Changes in SETD1A also raise the risk of a range of neurodevelopmental disorders, the researchers said. In a study published in the journal Nature Neuroscience, the team found that mutations that remove the function of SETD1A are almost never found in the general population, but affect 1 in 1,000 people with schizophrenia. While this gene fault explains only a very small fraction of all schizophrenia patients, it provides an important clue to the wider biology of the disorder, they said. Schizophrenia is a severe and common psychiatric illness that affects around one in 100 people worldwide. Symptoms include disruptions in thinking, language and perception, and patients can also suffer psychotic experiences such as hearing voices or having delusions. While the exact causes of schizophrenia are unknown, research to date suggests a combination of physical, genetic, psychological and environmental factors can make people more likely to develop it. Jeff Barrett, who led the study for the Sanger Institute, said its results were surprising and exciting. "Psychiatric disorders are complex diseases involving many genes, and it is extremely difficult to find conclusive proof of the importance of a single gene," he said. Mike Owen, a Cardiff University expert in neuropsychiatric genetics and genomics, said the so-far limited understanding of schizophrenia's causes has hampered efforts to develop new treatments. "Current drugs are only effective in alleviating some of the symptoms, can lead to troubling side effects and are ineffective in a sizeable minority of cases," he said. This new finding about defects in the SETD1A gene - although only explaining a small fraction of cases - may guide researchers towards new pathways that could be targets for treatments or medicines in a larger number of cases, Owen said. The study analysed the genome sequences of more than 16,000 people from Britain, Finland and Sweden, including those from 5,341 people with schizophrenia. Damage to the SETD1A gene was found in 10 of the schizophrenia patients, and surprisingly also in six other people with other developmental and neuropsychiatric disorders such as intellectual disability, the scientists said. This shows the same gene is involved in both schizophrenia and developmental disorders and suggests they may share common biological pathways.

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The data on TP53 mutations (including allele frequency) and CNVs in pan-tumours and AML are derived from The Cancer Genome Atlas (TCGA) data in the cBioPortal for Cancer Genomics (http://www.cbioportal.org/; accessed on 29 October 2014). Only sequenced samples with allele frequency information provided were included in our analysis. Considering potential normal tissue contamination, samples with TP53 mutation allele frequency above 0.6 were considered as a homozygous mutation. The SNP data were visualized in IGV and statistics for AML outcome were analysed in Prism 6. Since cBioPortal only has a few non-Hodgkin lymphoma cases available, we used published data to extract TP53 mutation and deletion information18, 30, 31, 32, 33, 34. Clinical outcomes were annotated from follow-up data available within the Gene Expression Omnibus GSE34171 series. CNV analysis was performed using published AML and DLBCL tumour copy number data in Affymetrix SNP Array 6.0 .cel format (http://cancergenome.nih.gov/)18, 35, 36, 37 according to GISTIC2.0 (ref. 14). Specifically, the following GISTIC parameters and values were used following the latest TCGA Copy Number Portal analysis version (3 November 2014 stddata__2014_10_17; http://www.broadinstitute.org/tcga/gistic/browseGisticByTissue): core GISTIC version 2.0.22; reference genome build hg19; amplification threshold 0.1; deletion threshold 0.1; high-level amplification threshold 1.0; high-level deletion threshold 1.0; broad length cut-off 0.50; peak confidence level 0.95; cap 1.5; gene-GISTIC, true; arm-level peel-off, true; significance threshold 0.25; join segment size 8; X chromosome removed, false; maximum segments per sample 2,000; minimum samples per disease 40. To create a conditional 11B3 chromosome deletion, the MICER strategy was used15. Briefly, MICER clones MHPN91j22 (centromeric to Sco1) and MHPP248j19 (telomeric to Alox12) (Sanger Institute) were introduced into AB2.2 ES cells (129S5 strain, Sanger Institute) by sequential electroporation, followed by G418 (neomycin; 180 μg ml−1) and puromycin (1 μg ml−1) selection, respectively. Successful recombination events were confirmed by Southern blotting using the hybridized probes designated in Supplementary Table 2 as described38. The cis- and trans-localizations of two loxP sites in doubly targeted ES cells were further distinguished by PCR with df-F and df-R, or dp-F and dp-R (Supplementary Table 2), respectively, after Adeno-cre infection and HAT (Gibco) selection. Correct cis-ES clones in which two loxP sites were integrated into the same allele were used to generate chimaera mice by blastocyst injection. The F1 pups were genotyped with 11B3-F and 11B3-R primers (Supplementary Table 2) and those positive backcrossed to C57BL/6 mouse strains for more than 10 generations. All of the mouse experiments were approved by the Institutional Animal Care and Use Committee at the Memorial Sloan Kettering Cancer Center. Eμ-Myc, Vav1-cre, Ella-cre, Trp53LSL-R270H/+, Trp53LSL-R72H/+, Trp53+/−, Trp53fl/+ and Rag1−/− mice were ordered from Jackson Laboratories21, 39, 40, 41, 42, 43, 44 and the Arf+/− mouse strain is a gift from C. Sherr45. Eμ-Myc mice with different Trp53 alterations were monitored weekly with disease state being defined by palpable enlarged solid lymph nodes and/or paralysis. Tumour monitoring was done as blinded experiments. For lymphoma generated by transplantation, 1 million Eμ-Myc HPSCs from embryonic day (E)13.5 fetal liver or autoMACS-purified B220+ B progenitor cells isolated from 6–8-week mouse bone marrow were transduced with retroviruses, followed by tail-vein injection into sublethally irradiated (6 Gy, Cs137) C57BL/6 mice (Taconic; 6–8-week old, female, 5–10 mice per cohort)11, 46. All recipient mice were randomly divided into subgroups before transplantation and monitored as described earlier. The generation of AML proceeded as previously reported29. Briefly, retrovirally infected c-Kit+ haematopoietic stem and progenitor cells were transplanted into sublethally irradiated (6 Gy, Cs137) C57BL/6 mice, followed by routine monitoring of peripheral blood cell counts and Giemsa–Wright blood smear staining. For secondary transplantation experiments, 1 million leukaemia cells were transplanted into sublethally irradiated (4.5 Gy) mice. The immunophenotypes of resulting lymphomas and leukaemias were determined by flow cytometry as previously reported using antibodies purchased from eBioscience11, 29. Statistical analysis of all survival data was carried out using the log-rank test from Prism 6. No statistical methods were used to predetermine sample size. MSCV-Myc-IRES-GFP and MLS-based retroviral constructs harbouring a GFP or mCherry fluorescent reporter and targeting Ren, Trp53, Eif5a, Nf1 or Mll3 have all been reported before11, 29, 47. For the tandem shRNA experiments performed in Fig. 3, mirE-based shRNAs targeting two different genes were cloned into an MLS-based vector in an analogous fashion to what has been previously described48, 49. Retrovirus packaging and infection of HSPCs was done as previously reported11, 29. B220+ cells were isolated from the bone marrow of 6-week-old Eμ-Myc mice by autoMACS positive selection with anti-B220 microbeads (Militeny Biotech). After overnight culture, cells were infected with retroviruses carrying the indicated shRNAs. Two days after infection, 0.5 × 106 cells were washed with PBS followed by annexin V buffer (10 mM HEPES, 140 mM NaCl, 25 mM CaCl , pH 7.4), and incubated at room temperature with Pacific Blue annexin V (BD Biosciences) and propridium iodide (PI; 1 μg ml−1; Sigma-Aldrich) for 15 min and analysed on a LSR II flow cytometer (BD Biosciences). For arachidonic acid treatment, pre-B cells were cultured out from bone marrow cells in pre-B cell medium (RPMI1640, 10% FBS, 1% penicillin/streptomycin, 50 μM β-mercaptoethanol, 3 ng ml−1 IL-7). After 3 days culture, pre-B cells were treated with a series concentration of arachidonic acid (Cayman Chemical) for 20 h, followed by annexin V staining as described earlier. Lymphoma cells isolated from lymph nodes of diseased animals were treated with vehicle (PBS) or 1 μg ml−1 adriamycin for 4 h. Whole cell lysates were extracted in cell lysis buffer (Cell Signaling Technology) supplemented with protease inhibitors (Roche), followed by SDS–PAGE gel electrophoresis and blotting onto PVDF membranes (Millipore). Eμ-Myc;Arf−/− lymphoma cell lines were used as a positive control for p53 induction. The p53 antibody used was obtained from Novocastra (NCL-p53-505) and horseradish peroxidase (HRP)-conjugated β-actin antibody from Sigma (AC-15). Alox15b expressions were examined in NIH3T3 cells, which were infected by shRNAs targeting Ren or Alox15b and then selected by G418. Anti-Alox15b antibody is from Sigma (SAB2100110), and HRP-conjugated GAPDH antibody is from ThermoFisher Scientific (MA5-15738-HRP). RNA-seq and data analysis were performed by the Integrated Genomic and Bioinformatics core at the Memorial Sloan Kettering Cancer Center. Briefly, total RNA from 11B3fl/Trp53fl;shNf1;shMll3;Vav1-cre or Trp53fl/fl;shNf1;shMll3;Vav1-cre leukaemia cells (four lines per cohort), isolated from the bone marrow of moribund mice, was isolated by Trizol extraction (Life Technologies). After ribogreen quantification (Life Technologies) and quality control on an Agilent BioAnalyzer, 500 ng of total RNA (RNA integrity number > 8) underwent polyA selection and Truseq library preparation according to instructions provided by Illumina (TruSeq RNA Sample Prep Kit v.2) with 6 cycles of PCR. Samples were barcoded and run on a Hiseq 2500 in a 50 bp/50 bp paired-end run, using the TruSeq SBS Kit v.3 (Illumina). An average of 45 million paired reads were generated per sample. At the most the ribosomal reads represented 0.1% and the percentage of mRNA bases was close to 65% on average. The output from the sequencers (FASTQ files) was mapped to the mouse genome (mm9) using the rnaStar (https://code.google.com/p/rna-star/) aligner, with the two-pass mapping methods. After mapping, the expression counts of each individual gene were computed using HTSeq (http://www-huber.embl.de/users/anders/HTSeq), followed by normalization and differential expression analysis among samples using the R/Bioconductor package DESeq (http://www-huber.embl.de/users/anders/DESeq). Gene set enrichment analysis (GSEA) was performed with Broad’s GSEA algorithm. A list of all primers used for PCR analysis is given in Supplementary Table 2. For detection and quantification of 11B3 recombination/deletion two methods were employed. In both cases genomic DNA (gDNA) was extracted from lymphoma or leukaemia cells using Puregene DNA purification kit (Qiagen). Initially, semi-quantitative PCR was used to detect the recombined 11B3 allele using primers df-F and df-R, generating a 2.2 kb product (Fig. 2d). The estimated frequency of recombination was determined by dropping gDNA from 11B3+/− into 11B3fl/+ at various ratios. For qPCR of the 11B3 deletion (Fig. 2e), SYBR Green PCR Master Mix (Applied Biosystems) was used and cycling and analysis was carried out on a ViiA 7 (Applied Biosystems). Primers 11B3-Q-F and 11B3-Q-R were used to detect the floxed allele, and to estimate the frequency of 11B3 deletion. Allelic frequency in UPD analysis (Extended Data Fig. 5a) was determined similarly, in this case with serial dilution of wild-type gDNA into DNase-free water to construct a standard curve. Two-tailed t-test is used for statistics analysis by Prism 6. For p21 gene expression examination by RT–qPCR, RNA was isolated with Trizol, cDNA was synthesized with SuperScript III First-Strand Synthesis System (Life Technologies) and qPCR was performed as described earlier with primers p21-Q-F and p21-Q-R. Trp53 exons (2–10) were amplified from genomic DNAs of 11B3-deleted lymphomas by PCR (see Supplementary Table 2 for primer sequences) and subjected to Sanger sequencing. Mutations were called only if detected in sequencing reads carried out in the forward and reverse direction. SNP analysis of isolated lymphoma (tumour) or tail (normal) genomic DNAs from the same tumour-bearing mouse were carried out by Charles River laboratory. Briefly, a SNP Taqman assay with competing FAM- or VIC-labelled probes was used to detect the relevant C57BL/6 and 129S SNPs (D11Mit4 and D11NDS16) as described previously50. Genomic DNA was extracted from freshly isolated lymphoma cells from one Eμ-Myc;11B3fl/+;Vav-cre mice. One microgram of DNA was sonicated (17 W, 75 s) on an E220 sonicator (Covaris). Samples were subsequently prepared using standard Illumina library preparation (end repair, poly A addition, and adaptor ligation). Libraries were purified using AMPure XP magnetic beads (Beckman Coulter), PCR enriched, and sequenced on an Illumina HiSeq instrument in a multiplexed format. Sequencing reads per sample were mapped using Bowtie with PCR duplicates removed. Approximately 2.5 million uniquely mappable reads were further processed for copy number determination using the ‘varbin’ algorithm51, 52 with 5,000 bins, allowing for a median resolution of ~600 kb. GC content normalization, segmentation and copy number estimation was calculated as described53. A custom shRNA library was designed to target mouse homologues (six shRNAs for one gene) to all human protein-coding genes on chromosome 17p13.1 from ALOX12 to SCO1, except TP53 and EIF5A. shRNAs were cloned into a retrovirus-based vector MLS by pool-specific PCR as previously described11. Eμ-Myc HSPCs infected with pooled shRNAs were transplanted into sublethally irradiated recipient mice. Resulting tumours were harvested, and used to extract contained shRNAs, followed by HiSeq in HiSeq 2500 (Illumina). Twenty-two oligonucleotides of shRNAs used in this study are listed in Supplementary Table 3. Total lipids were extracted using Folch’s method54 and analysed by LC-MS as previously described55. Briefly, freshly harvested cells were homogenized by chloroform/methanol (2:1, v-v). After being washed by water, the lipid-containing chloroform phase is evaporated. Dried lipids were dissolved in 100 μl 95% acetonitrile (in H O), sonicated for 3–5 min, and spiked with 10 μl of 500 ng ml−1 deuterated internal standard solution (IS; arachidonic acid-d8; Cayman Chemical, 390010). Then, 5 μl samples were injected into Acquity ultra performance liquid chromatography (UPLC) system (Waters), equipped with Acquity UPLC BEH C18 column (100 mm × 2.1 mm I.D., 1.7 μm; Waters). Samples were washed through the column with a gradient 0.1% formic acid: acetonitrile mobile elution from 35:65 (v:v) to 5:95 for 10 min. Flow rate was 0.25 ml min−1. Right after HPLC, samples were analysed in a Quattro Premier EX triple quadrupole mass spectrometer (Waters), which has electrospray negative mode and MasslynxV4.1 software. For each run, a standard curve was generated with different concentration of arachidonic acid lipid maps MS standard (Cayman Chemical, 10007268) mixed with IS (50 ng ml−1 final concentration). Arachidonic acid standard m/z is 303.2, and IS is 311.3. Three Eμ-Myc lymphoma cell lines generated from Trp53fl/+;Vav1-cre or 11B3fl/+;Vav1-cre tumour-bearing mice were cultured in BCM medium (45% DMEM, 45% IMDM, 10% FBS, 2 mM glutamine, 50 μM β- mercaptoethanol, 1× penicillin/streptomycin) in 96-well plates. Cells were treated with the indicated concentrations of 4-hydroxycyclophosphamide (Toronto Research Chemicals) or vincristine (Bedford Laboratories) for 3 days. The number of living cells was determined by PI staining and cell counting on a Guava EasyCyte (EMD Millipore). Leukaemia cell lines from Trp53∆/∆ or 11B3∆/Trp53∆;shNf1;shMll3 mice were treated with cytarabine (araC; Bedford Laboratories) or JQ1 (a gift from J. Bradner) in stem cell medium (BCM medium supplemented with 1 ng ml−1 IL-3, 4 ng ml−1 IL-6 and 10 ng ml−1 SCF) and cell viability after 3 days was determined similarly. All cytokines are from Invitrogen.

This research, published in the journal Nature Microbiology, also charts the development of the pathogen's resistance to antibiotics. Scientists from the Wellcome Trust Sanger Institute, Institut Pasteur in Paris and international collaborators have uncovered hitherto unknown links between the various outbreaks that have occurred through history. One of the worst scourges to afflict humans throughout the 18th and 19th centuries, dysentery was transmitted from one continent to another via migratory movements and military operations. The bacterium Shigella dysenteriae type 1, causes life-threatening bloody diarrhoea, and has been responsible for thousands of deaths, especially amongst children in the developing world. The last big epidemic in Central America killed 20,000 people between 1969 and 1972. Despite the isolation of S. dysenteriae strains globally, the origin of each dysentery epidemic and the links between them has remained unclear. To provide a detailed understanding of this disease, a team of scientists led by Prof Nicholas Thomson from the Wellcome Trust Sanger Institute, and senior author Dr François-Xavier Weill from the Institut Pasteur undertook a huge genomic study using high throughput technologies for bacterial genome sequencing and bioinformatics. They analyzed more than 330 strains of S. dysenteriae type 1 isolated between 1915 (in soldiers taking part in the First World War Gallipoli campaign) and 2011. The strains had been collected by 35 international institutes in 66 countries. The team found that the type 1 strain has existed since at least the eighteenth century, and spread throughout the globe. Contrary to popular belief, the study showed that the S. dysenteriae pathogen currently endemic in Africa and Asia is of European origin. Prof Nicholas Thomson, leader of the Bacterial Genomics and Evolution group at the Sanger Institute, said: "Analyzing the full genomes of all these Shigella dysenteriae strains collected over a huge timeframe and from such an array of different countries provided us with an unprecedented insight into the historical spread of this pathogen. This was needed because there are still many unanswered questions relating this infamous and important bacterial pathogen. It was achieved by combining high resolution genomic research data with the detailed information recording the provenance of each sample from a large number of dedicated groups." By identifying different genetic lineages, the scientists were able to trace the path of the bacterium worldwide over time, showing that European colonialism and migration helped spread the pathogen. European S. dysenteriae spread to America, Africa and Asia between 1889 and 1903, aided by European emigration to America and the colonization of territories in Africa and Asia. The bacterium reappeared in Europe during the First and Second World Wars, before dying out in Europe. However, it continued to spread across Asia, Africa and Central America with violent outbreaks, and several epidemic waves then spread to Africa and South-East Asia from the Indian subcontinent. Since the first bacteria were isolated well before the use of antibiotics, study of the collection has revealed that the first antibiotic resistance appeared in Asia and America in the mid-1960s. The bacterium then acquired resistance genes against most classes of antibiotics - fewer than 1 per cent of bacterial strains have remained susceptible to antibiotics since the 1990s. Scientists consider it inevitable and a cause for concern that dysentery bacteria will acquire resistance to the last-resort antibiotic classes. Dr François-Xavier Weill, Research Director at the Enteric Bacterial Pathogens Unit, Institut Pasteur, said: "This bacterium is still in circulation, and could be responsible for future epidemics if conditions should prove favorable - such as a large gathering of people without access to drinking water or treatment of human waste. This study highlights the need for an effective vaccine, which will be crucial for controlling this disease in the future in view of the reduced efficacy of antibiotics." More information: Global phylogeography and evolutionary history of Shigella dysenteriae type 1, DOI: 10.1038/nmicrobiol.2016.27

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A new method by researchers in the UK and Belgium makes it possible to study the epigenome and transcriptome of a single cell at the same time. The protocol, published in Nature Methods, helps scientists pinpoint the relationship between changes in DNA methylation and gene expression. Single-cell sequencing technology has progressed rapidly in recent years, and is widely used to study how gene expression profiles ('transcriptomes') vary between cells. Recent single-cell protocols also allow researchers to explore chemical modification of DNA ('epigenetics'), for example DNA methylation, which is a driving force behind changes to gene expression. Until now, it has only been possible to study single-cell transcriptomes and epigenomes separately. "This new experimental protocol lets you assay both DNA methylation and RNA of the same single cell in parallel," says Oliver Stegle of EMBL's European Bioinformatics Institute (EMBL-EBI). "Our approach provides the first direct view on the relationship between heterogeneity in DNA methylation and variation of expression in specific genes across single cells." "This method combines our previously developed protocol for parallel DNA and RNA sequencing with new advances in single-cell epigenetics," explains Thierry Voet of the Wellcome Trust Sanger Institute and Katholieke Universiteit Leuven, Belgium. "The result is an optimised approach that maximises the amount of biological information that can be obtained from a single cell." To test the method (called scM&T-seq), the group used mouse embryonic stem cells (ESCs) at a stage when they switch continuously between different gene-expression states. Just as in the cells of an early stage embryo, the identity of these cells is fluid rather than fixed. The researchers used two techniques in parallel: one that reveals detailed information about expression (how much variation there is, where that heterogeneity is coming from) and one to study DNA methylation in the same cells. For each cell, they obtained sufficient coverage to study epigenetic and transcriptome diversity of several thousand genes. "The epigenetic state of ESCs is highly variable, and this variation is associated with changes in gene expression," explains Wolf Reik of the Babraham Institute and Wellcome Trust Sanger Institute. "Much of the transcriptional variability we see is thought to be driven by modifications of DNA, but now we have a technique that allows us to look at a single cell and discover relationships between DNA methylation and gene expression that were previously unknown. To understand development, it is really important that we pin these relationships down, and get them right." "Our statistical approach revealed hundreds of individual associations between variable epigenetic regions and gene expression," adds Christof Angermueller of EMBL-EBI. "These associations can provide important insights into how pluripotency is maintained and how cell differentiation is regulated." Going forward, the researchers expect the new protocol to offer new opportunities to study multiple different molecular layers simultaneously. This will go a long way towards understanding the connection between gene expression and DNA methylation in single cells, and identifying the factors that influence this relationship. Such research has implications for understanding normal development, and changes that occur with ageing and cancer. The method was developed within the Sanger Institute/EMBL-EBI Single Cell Genomics Centre, a collaborative effort to develop single-cell technologies and apply them to new biological questions.

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