Ribosomal DNAs (rDNAs) are arranged in purely tandem repeats, preventing them from being reliably assembled onto chromosomes during generation of genome assembly. The uncertainty of rDNA genomic structure presents a significant barrier for studying their function and evolution.C. elegans and C. briggsae. We classify the individual rDNA’s repeating units into 25 types based on the unique sequence variations in each unit of C. elegans (N2). We next perform assembly of the cluster by taking advantage of the long reads that carry these units, which led to an assembly of 5S rDNA cluster consisting of up to 167 consecutive 5S rDNA units in the N2 strain. The ordering and copy number of various rDNA units are consistent with the separation time between strains. Surprisingly, we observed a drastically reduced level of variation in the unit composition in the 5S rDNA cluster in the C. elegans CB4856 and C. briggsae AF16 strains than in the C. elegans N2 strain, suggesting that N2, a widely used reference strain, is likely to be defective in maintaining the 5S rDNA cluster stability compared with other wild isolates of C. elegans or C. briggsae.Here we generate ultra-long Oxford Nanopore Technologies (ONT) and short NGS reads to delineate the architecture and variation of the 5S rDNA cluster in the different strains of The results demonstrate that Nanopore DNA sequencing reads are capable of generating assembly of highly repetitive sequences, and rDNA units are highly dynamic both within and between population(s) of the same species in terms of sequence and copy number. The detailed structure and variation of the 5S rDNA units within the rDNA cluster pave the way for functional and evolutionary studies.The online version contains supplementary material available at 10.1186/s12864-022-08476-x. C. elegans, each 5S rDNA repeating unit contains a 5S rRNA gene, a splicing leader gene (SL1), and two non-transcribed sequences (NTS). The 18S, 5.8S, and 28S rRNAs are produced as a single transcript using 45S rDNA as a template, which is also arranged as a tandem array in the genome. The transcript is processed into three individual RNAs following transcription  V), ZZY0603 (unc-119(tm4063) III; Is V), and ZZY0653 (unc-119(tm4063) III; Is I), each carrying a single-copy of transgene in 5S rDNA cluster. For C. briggsae wild isolate, genomic DNAs were extracted from AF16 young adults. Animal synchronization was performed as described [C. elegans and C. briggsae animals were maintained on plates of 1.5% nematode growth medium (NGM) seeded with E. coli OP50 at room temperature and in a 25 °C incubator, respectively. Genomic DNAs were extracted from animals with PureLink Genomic DNA Mini Kit (Invitrogen) using siliconized tubes and pipette tips to minimize shearing. 4 μg purified DNAs from each sample were used for library preparation using Genomic DNA by Ligation Kits SQK-LSK108 (ONT) for N2a and ZZY0653, and Ligation Kits SQK-LSK109 (ONT) for the remaining strains. Sequencing was performed on GridION X5 or MinION with R9.4.1 flow cell  using default parameters.The details of ONT sequencing libraries from this study and previous studies for different strains were listed in the Tables escribed . Before C. elegans N2 genome assembly (WormBase WBcel235) [C. briggsae AF16 genome assembly (CB4) [C. elegans VC2010, a wild-type strain derived from N2, were downloaded from European Nucleotide Archive (ENA) with accession numbers PRJEB22098 [C. elegans strain PD1074, a wild type strain derived from VC2010, were downloaded from Sequence Read Archive (SRA) database with accession number SRR7594463 and SRR7594465, respectively [C. elegans CB4856 were downloaded from the SRA database with accession number SRR8599837 [Base-callings were performed using Guppy  using the high-accuracy configuration model. All the base-called reads from each library were pooled for analysis of read length distribution with SeqKit (v0.10.2) . The reaBcel235)  or the Cly (CB4)  with Minly (CB4)  using dely (CB4) . The ONTJEB22098 . The ONTectively . The ONTR8599837 .C. elegans N2a and CB4856, the alignment BAM files were downloaded from Caenorhabditis elegans Natural Diversity Resource (CeNDR) project [C. briggsae SLR reads and Hi-C reads were downloaded from the SRA database with accession number SRR6384296 and SRR6384332, respectively [For short NGS reads of  project . The C. ectively , 32.C. elegans ONT reads with rDNA sequences were aligned against a single copy of cel-5S unit 1.1 with Minimap2. From the CIGAR strings in the generated SAM file, to minimize the INDELs resulting from base-calling errors for homopolymers and simple repeats, only the INDELs longer than 3 bp were kept for copy counting with custom scripts. After normalization with genome-wide read coverage, the normalized INDEL count higher than one copy was considered as a potential new INDEL variant. Two types of deletion were identified in N2a strain only, one carrying a 4-bp deletion and other a 30-bp deletion  were used for multiple alignment and construction of phylogenetic tree with CLC Sequence Viewer  using following parameters: gap open cost: 10.0; gap extension cost: 1.0; and alignment mode: very accurate. Neighbor joining phylogenetic trees of 5S rDNA units from each species were generated with Jukes-Cantor distance measure with 1000 replicates of bootstrapping. The individual 5S rDNA unit variants was named based on their relatedness to the cel-5S unit 1.1 in the tree  units are present in all C. elegans wild isolates, the NGS reads derived from 330 whole-genome shotgun sequencing libraries [C. elegans 5S rDNA that carry the 30-bp deletion, i.e., unit 1.1 and 1.24, using BWA (v0.7.17) [C. elegans CB4856 strain and C. briggsae AF16 strain were identified similarly as those in the C. elegans N2a strain.To investigate whether the 30-bp deletion in the ibraries  were mapv0.7.17) . The reav0.7.17)  was visuv0.7.17) –84. The C. elegans 5S rDNA cluster started with identifying all the ONT reads carrying the flanking sequences of the cluster, i.e. the ZK218.23 as the left boundary, and the sequences from chrV: 17,133,740-17,137,381 (WBcel235) as the right boundary. These reads were iteratively extended into the cluster by performing SNP- and INDEL-based manual assembly. Based on the pairwise alignment results using BLASTN [C. elegans N2a-derived strains and between C. elegans strains, each 5S rDNA cluster was similarly assembled with strain-specific ONT reads. For assembly of the 45S rDNA cluster in C. elegans N2a, the right boundary was determined using the ONT reads containing both ETS and telomere sequences (TTAGGC). For C. elegans CB4856 45S rDNA cluster, the right boundary was determined using the ONT reads containing telomere sequences.Reconstruction of the g BLASTN , the conC. briggsae 5S rDNA cluster was started with two chromosome III contigs carrying a 5S rDNA sequence and genes next to rDNA sequences (CBG06809 and CBG10685). The right boundary of 45S rDNA cluster was determined with the ONT reads carrying the rDNA sequence and those from its right boundary in CB4, which is located at the beginning of chromosome V. The 45S cluster left boundary was determined with the ONT reads carrying both 45S rDNA and telomere sequences.Reconstruction of the C. briggsae rDNA clusters, an AF16 draft genome was de novo assembled with ONT reads using Miniasm (v0.3). The resulting contigs were polished with Racon (v1.4.10) [C. briggsae genome (CB4) as a reference and interspaced with 1000 “Ns”. The final draft genome was aligned against CB4 using LAST (v1021) [C. briggsae genome assembly, and the C. elegans N2 genome assembly (WBcel235) was assessed in parallel using BUSCO (v4.0.2) [To get a better reference genome for locating v1.4.10)  two rounv1.4.10) . Bacteri (v1021) . The com(v4.0.2)  with nemC. elegans 5S rDNA units, the ONT reads mapped to the genomic interval of chrV: 17,110,000-17,430,000 (WBcel235) were extracted with SAMtools and were used for statistical analysis with SeqKit. The extracted reads were aligned against the 5S rRNA-coding sequence (referred to as 5S rRNA gene) with BLASTN with option “-word_size 7”. Sequences with alignment length > 17 bps were kept for the downstream analysis. The copy number of the 5S rDNA units was estimated for each library by dividing the summed read lengths aligned to 5S rRNA gene by the product between 5S RNA gene length (119) and genome-wide read coverage. For estimation of copy number of C. elegans 45S rDNA units, the reads mapped to the genomic interval of chrI: 15,057,500-15,072,434 (WBcel235) were extracted and aligned against the ITS1. Sequences with alignment length > 21 bps were kept for subsequent analysis. The copy number of the 45S rDNA units was estimated for each library by dividing the summed read lengths aligned to 45S rRNA gene sequence by the product between ITS1 length (464) and genome-wide read coverage.For estimation of copy number of C. briggsae 5S rDNA units, the reads mapped to the genomic interval of chrIII: 10,555,000-10,660,000 (C. briggsae CB4) were extracted. The extracted reads were aligned against the 5S rRNA gene sequence and two existing 5S rDNA units with BLASTN. Reads were retained for further analysis if the alignment size was bigger than 17, 170 and 170 bps for the 5S RNA gene, cbr-5S unit 1.1 and cbr-5S unit 2.1, respectively. The copy number of the 5S rDNA units was calculated in the same way as that in C. elegans. To extract all the reads mapped to the C. briggsae 45S rDNA cluster, a pseudo-chromosome was generated using chromosomal interval of chrI: 395,000-417,500 (CB4), which contains partial 26S rRNA gene and its flanking sequences consisting of five protein-coding genes and 100 copies of the C. briggsae 45S rDNA unit derived from SLR reads [cbr-ITS1 sequence with BLASTN. The copy number of the C. briggsae 45S rDNA unit was calculated in the same way as that in C. elegans.For copy number estimation of LR reads . Reads mC. elegans N2a and C. briggsae AF16, the Hi-C sequencing data from L1 stage animals [C. elegans reads, an rDNA pseudo-chromosome, which contains 50 copies of cel-5S unit 1.1 or 10 copies of cel-45S rDNA, was added into the reference genome for mapping of Hi-C reads. After trimming reads with Trimmomatic (v0.35) [C. briggsae was performed in the same way as that in C. elegans. Specifically, the rDNA pseudo-chromosomes consisting of 50 copies of cbr-5S unit 1.1, or 50 copies of cbr-5S unit 2.1 and unit 2.2 with mixed arrangement, or 10 copies of cbr-45S rDNA, were individually added to the C. briggsae genome assembly CB4, respectively, for mapping of C. briggsae Hi-C reads [To validate the genomic localization of the assembled rDNA clusters in the  animals , 87 were (v0.35) , the rem (v0.35)  with def (v0.35) , 90. The-C reads .To evaluate the structure of the newly assembled 5S rDNA clusters, the existing rDNA cluster sequences in the reference genome were replaced by the new assembly of rDNA sequences consisting of the minimum estimated copy number. The ONT reads were mapped against the modified reference genomes incorporated with the newly assembled rDNA cluster using Minimap2 with default parameters. The coverage within the new rDNA cluster was visualized in R with the ggplot2 package .miniMos targeting vector pCFJ909 [his-24 that was fused to the GFP coding sequence at its 5′ end to facilitate nuclear localization, as previously described [pie-1 3′ UTR as described previously [miniMos technique with the transgene insertion site being determined using inverse PCR [All promoter fragments were amplified from N2a genomic DNAs with PCR primers listed in Table S pCFJ909  was modiescribed . The fuseviously . The vecerse PCR . All theAdditional file 1.Additional file 2.Additional file 3.Additional file 4.Additional file 5.Additional file 6.Additional file 7.Additional file 8.Additional file 9.Additional file 10.Additional file 11.


The combined treatment with the H4R antagonist  reversed the effects of the H4R ligands. Importantly, we screened a drug repurposing library of 433 FDA-approved compounds (1 μM) in combination with histamine (10 μM) in Hut78 cells. Histamine produced a favorable antitumor effect with 18 of these compounds, including the histone deacetylase inhibitor panobinostat. Apoptosis, proliferation, and oxidative stress studies confirmed the antitumoral effects of the combination. We conclude that the H4R is expressed in TCL, and it is involved in histamine-mediated responses.The discovery of the human histamine H4 receptor (H4R) has contributed to our understanding of the role of histamine in numerous physiological and pathological conditions, including tumor development and progression. The lymph nodes of patients with malignant lymphomas have shown to contain high levels of histamine, however, less is known regarding the expression and function of the H4R in T-cell lymphoma (TCL). In this work we demonstrate the expression of H4R isoforms (mRNA and protein) in three human aggressive TCL . Histamine and specific H4R agonists (VUF8430 and JNJ28610244) significantly reduced cell viability in a dose-dependent manner ( T-cell lymphomas (TCL) constitute a heterogeneous group of non-Hodgkin lymphomas (NHL) with a complex diagnosis and relatively low incidence, representing around 10–15% of NHL in the Western world. Lymphomas that arise from mature T cells can be categorized together under the general term peripheral TCL (PTCL). Based on the World Health Organization (WHO), they are divided into three categories  and are classified in subtypes that include PTCL-NOS (not otherwise specified), anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), and natural killer/T-cell lymphoma (NKTCL) among other rare diseases. Cutaneous TCL (CTCL) are a subclass of extranodal lymphomas that arise within the skin, including Mycosis fungoides and Sézary syndrome ,3.Although there are various therapeutics currently available, durable disease control is challenging, especially in advanced-stage TCL that is associated with a poor prognosis. Histone deacetylase inhibitors (HDACi) are an emerging class of antitumor agents with the ability to regulate transcriptional and gene expression patterns and cytotoxicity ,5,6. HDAH4R gene generates possible splice variants. The complete sequence encodes 390 amino acids of full-length H4R(390) protein. Shorter isoforms do not bind histamine and might elicit modulatory effects on H4R signaling. However, their pathophysiological relevance is still unknown [Histamine is a biogenic amine involved in numerous pathophysiological conditions, including the regulation of hematopoiesis and hematological malignancies ,10,11. T unknown ,16,17. I unknown ,19,20,21 unknown ,23,24,25 unknown .Histamine is the endogenous receptor agonist and binds to the H4R with high affinity. However, this biogenic amine has cross-reactivity with all four histamine receptor subtypes. Soon after H4R discovery, numerous H4R ligands (agonists and antagonists) were developed attempting to identify the pharmacological profile and function of the H4R. The indole carboxamide compound JNJ7777120 was the first reported selective and potent H4R antagonist, and it has been broadly used as the reference pharmacological agent to determine the role of H4R in several in vitro and in vivo experimental models of disease ,12,14,15Although it was previously reported that histamine levels in lymph nodes of patients with malignant lymphomas (Hodgkin’s disease and NHL) are higher compared to control individuals , limitedThe aim of the present work was to investigate the expression of the H4R in TCL, and to evaluate the potential antitumor effects of histamine and H4R ligands. We show that H4R isoforms are expressed in TCL and are involved in histamine-mediated responses. Histamine could be an attractive compound for its use as a single agent or in combination with HDACi for the treatment of TCL.H4R gene in tumors of TCL patients [H4R(390) was found in CTCL and the most common subtypes of PTCL (H4R(302) was additionally detected only in a few samples  (44 kDa) and the splice variant isoform H4R(302) (34 kDa) [(390) isoform compared to Karpas299 and OCI-Ly12 TCL cells while Karpas299 has significantly higher levels of H4R(302) than the other TCL cells. Both HuT78 and OCI-Ly12 cells show significantly increased levels of H4R(390) compared to H4R(302) isoform  recognizes regions within amino acids 1–52, which is present in the H4R protein isoforms. As shown in (34 kDa) ,16,17, a(34 kDa) . HuT78 c isoform B,C.H4R isoforms at the mRNA level. The primers were designed to amplify individually each H4R isoform’s transcript. High expression of the H4R(390) isoform mRNA at similar levels was observed in HuT78, Karpas299, and OCI-Ly12 TCL cells (H4R(302) isoform mRNA expression exhibited different levels, depending on the cell line (H4R(302) isoform compared to HuT78 and OCI-Ly12 cells (H4R(67) isoform mRNA showed the lowest expression level in all cell lines compared to the other two isoforms (We further investigated the expression of CL cells D. In conell line E. Karpas12 cells E. Truncaisoforms F.We next investigated whether histamine and the specific H4R agonists JNJ28610244 (JNJ28) and VUF8430 can modulate cell viability. Results demonstrate that histamine, JNJ28, and VUF8430 significantly decreased cell viability in a dose-dependent manner in HuT78 cells after 48 h of treatment. Similar results were found in H4R agonist-treated Karpas299 D–F and OTo corroborate the biological significance of H4R in TCL cell lines, we next analyzed the apoptotic regulation induced by histamine, JNJ28, and VUF8430. The treatment of HuT78 cells with histamine (10 µM), JNJ28 (10 µM), or VUF8430 (10 µM) for 48 h increased the percentage of apoptotic cells evaluated by Caspase-Glo 3/7 Assay A. The apAccording to the Western blot analysis, HuT78 cells exhibited the highest expression level of the full length and biologically active isoform of the H4R (390 aa) compared to the other cell lines. Therefore, we decided to deepen the evaluation of the therapeutic efficacy of histamine and H4R’s ligands in these TCL cells.H4R expression, the mRNA expression of the three isoforms were analyzed upon histamine (10 µM) and VUF8430 (10 µM) treatment for 30 min in HuT78 cells. As depicted in H4R(390) isoform’s expression, an effect that was blocked with the treatment with JNJ77 (10 µM). A similar pattern of expression was observed for the H4R(67) isoform (H4R(302) isoform (To elucidate whether H4R ligands’ treatment could modulate  isoform C. Howeve isoform B.We next exposed HuT78 cells to a drug screening library consisting of 433 compounds (SelleckChem) . Cells wThe antitumoral effect of the combination was confirmed evaluating apoptosis, proliferation, and oxidative stress parameters. Results demonstrated that histamine (10 µM) and panobinostat (1 µM) significantly decreased HuT78 cell viability and count after 48 h of treatment. Moreover, histamine enhanced panobinostat-induced effect on cell viability and proliferation C,D. SimiFinally, we evaluated whether histamine in combination with HDACi could regulate the ROS levels in HuT78. As it is shown in H4R gene is mapped on chromosome 18q11.2, and it is made up of three exons separated by two large introns. H4R encodes a 390 amino acid protein with an estimated molecular weight of 44 kDa. Alternative splicing of the gene can occur, and two lower molecular weight isoforms have been described. The H4R(302) isoform of 302 amino acids, has an interior deletion between transmembrane domains II and IV and a molecular weight of 31–34 kDa. The truncated H4R(67) isoform of 67 amino acids consists of the transmembrane domains I and part of the II [At the beginning of the millennium, the H4R was discovered independently by numerous scientific groups of the academy and industry. H4R is predominantly expressed in cells of the immune system such as mast cells, basophils, eosinophils, dendritic cells, Natural Killer cells, and T lymphocytes, and it exhibits functional implications in inflammatory diseases and immunomodulatory pathways ,38,39,40f the II ,17,36.H4R in human TCL samples. We validated the H4R expression in HuT78, Karpas299, and OCI-Ly-12 TCL cell lines. The full length H4R and the two alternatively spliced isoforms were differentially expressed in the three TCL cells. Western blot analysis shows the predominant expression of H4R(390) and H4R(302) isoforms. Additional bands were occasionally detected, which could likely represent oligomerization forms, unglycosylated or heavily glycosylated forms of the H4R [H4R(390) full length isoform and the H4R splice variants are differentially expressed in the TCL cell lines. The H4R(390) was highly expressed in the three cell lines, while splice variant mRNA H4R(302) was more abundant in the Karpas299 cells compared to the other cells, which is in line with the protein expression levels determined by Western blot. The lower abundance of the mRNA of the truncated splice variant H4R(67) in all cell lines could be related to the abundant expression of full length form [In the present work, we show the mRNA expression of  the H4R . In agregth form . The spegth form ,17. Verygth form ,17. TherH4R(390) and H4R(67) were upregulated while H4R(302) isoform exhibited no changes upon histamine and H4R agonist treatments in HuT78, which might offer insight into the functional role and regulation of this receptor.A more detailed mRNA expression analysis demonstrated that To explore the role of histamine-induced activation of the H4R in TCL cells, we investigated its effects on cell viability and apoptosis using a pharmacological approach. Histamine and specific H4R agonists produced a dose dependent decrease in cell viability in the three TCL cell lines. This antitumor effect is associated with an increase in apoptotic cell death. Both the proapoptotic and the cytotoxic effects were prevented by the combined treatment with the H4R antagonist JNJ7777120, confirming that histamine-induced actions are primarily mediated by the H4R. Recent evidence shows that histamine through H4R plays important roles at a variety of stages during tumor development and progression, producing protumoral or antitumoral effects depending on the cancer cell type. Although in colon cancer the activation of H4R induced cell proliferation and VEGF expression, in other cancer subtypes including, melanoma, cholangiocarcinoma, oral squamous cell carcinoma, and breast, esophageal and lung cancers, histamine via H4R reduced proliferation, epithelial to mesenchymal transition, or tumor spread ,40,41,42Martnet et al., (2015) reinforced the hypothesis that histamine is involved in lymphoma progression. In vivo histamine treatment reduced the tumor growth of murine lymphoma developed with EL-4 TCL cells, inducing the intratumoral accumulation of maturated dendritic cells . FurtherThe prognosis of advanced TCL is poor and characterized by aggressive behavior with little response to chemotherapy ,2,3. TheSeveral clinical trials were performed with IL-2 immunotherapy combined with histamine for solid neoplastic diseases and hematopoietic cancers with promising results. This combination therapy improved leukemia-free survival and was approved in Europe for the treatment of adults with AML ,48,49,50A strategy that could help to identify new medical indications for approved drugs consists of drug repurposing . To idenHDACi produces multiple antitumor effects that include cell cycle arrest, induction of apoptosis, inhibition of angiogenesis, and decreased invasion and metastasis ,61. The Histamine ; H4R agonist: VUF8430 ; JNJ28610244 (JNJ28) . H4R antagonist: JNJ7777120 (JNJ77) (Janssen Research & Development). Panobinostat were from Selleckchem .RNA-seq data from tumors of PTCL patients were obtained from the NCBI Sequence Read Archive (SRA), accession numbers: SRP029591 , SRP0447Data was filtered and quality checked with fastp v0.20.0 . Transcr2.HuT78 cells  and HEK293T  were obtained from ATCC. OCI-Ly12  was obtained from the Ontario Cancer Institute. Karpas299  was obtained from the DMSZ. HEK293T cells were cultured in DMEM  supplemented with 10% FCS, 100 U/mL penicillin and 100 µg/mL streptomycin . Other cell lines were cultured in RPMI-1640 medium, supplemented with 10% FCS and 2 mM glutamine (complete medium). Cultures were grown at 37 °C in a humidified air atmosphere containing 5% COTBP (Tata Box Binding Protein) was used as an internal control. Primer sequences for PCR were as follows: H4R(390), 5′-ACTTGGCCATCTCTGACTTCT-3′ (forward) and 5′-CATTCGAACAGCGTGTGAGG-3′ (reverse); H4R(302) 5′-TGACTTCTTTGTGGTTTCAGAGT-3′ (forward) and 5′-GGCAAGGATGTACCATTCCG-3′ (reverse); H4R(67) 5′-CTCTGACTTCTTTGTGGGTGTCT-3′ (forward) and 5′-AACGGCCACCATCAGAGTAAC-3′ (reverse). qRT-PCR reactions were carried out in triplicates (intra- and inter-assays by triplicate). Fold change in gene expression was calculated using the ΔΔCT method.Cells were cultured as indicated above. After incubation, RNA was isolated from cell lines using TRIzol reagent (Invitrogen) and measured using the Nanodrop 1000 spectrophotometer. Equal amounts of RNA were converted to cDNA using Verso cDNA Synthesis Kit . The synthesized cDNAs were used immediately for PCR amplification or stored at −80 °C for later use. qRT-PCR was performed in 384-well plates using a 7900 HT fast real-time PCR system . 3VO4, 1 mM NaF and 10 mM Na2PO7), and centrifuged at 14,000× g for 20 min at 4 °C. The supernatant was stored at −80 °C until use. The protein concentration was measured by using the method of BCA protein assay.Cells were incubated as above indicated, washed twice with cold PBS, scraped with cold extraction buffer  containing the protease inhibitor cocktail (5 mL of cocktail/20 g of cell extract) plus phosphatase inhibitors (2 mM Nav/v). The membranes were washed three times with TBS plus Tween-20 (0.05% v/v) for 5 min and incubated for 1 h with goat IgG anti-rabbit antibody coupled to horseradish peroxidase  , washed three times with TBS plus Tween-20 and developed. As internal controls, membranes were re-incubated for 3 h with primary monoclonal antibody against α-tubulin  , washed three times as above indicated, and then incubated for 1 h with goat IgG anti-mouse antibody coupled to horseradish peroxidase  . We used ECL Western Blotting Substrate (Pierce Biotechnology) according to the manufacturer’s instructions and the blots were visualized by autoradiography. Quantitative densitometry analysis of Western blot bands was performed employing ImageJ version 10.2 . The normalized relative densities were calculated relative to the expression of α-tubulin.Total protein extracts (30–50 µg of proteins) were separated on a denaturing SDS-PAGE (15%) and transferred to nitrocellulose membranes. Membranes were blocked with BSA 5% in TBS 1 h and then incubated ON with primary polyclonal antibody against H4R   was determined using a luminometer .Cell viability was measured with a fluorometric resazurin reduction method . Briefly, 5 × 104 cells/well) and treated with 10 μmol L−1 histamine, 1 μmol L−1 panobinostat or both for 48 h. Phosphatidylserine exposure on the surface of apoptotic cells was determined by staining with Annexin-V FITC and PI (50 μg/mL)  by using flow cytometry, according to the manufacturer’s instructions and previously reported. Samples were run on a BD Accuri C6 flow cytometer (BDB), and data were analyzed by using the BD Accuri C6 software (BDB).Cells were seeded into 12-well plates  following manufacturer’s instructions. HuT78, OCI-Ly12, and Karpas299 cell lines were treated as indicated in results. Luminescence was measured using the Synergy4 microplate reader .4 cells/well), and were treated or not with 10 μM of histamine for 72 h. To determine the cell viability, we used the homogeneous method CellTiter-Glo® Luminescent Cell Viability Assay  following manufacturer’s instructions. It is based on quantification of the ATP present, which signals the presence of metabolically active cells. Luminescence was measured using the Synergy4 microplate reader (BioTek).Plates with the library of 433 FDA-approved compounds from Selleckchem’s anticancer drug library . HuT78 c2, 3.7 mM NaH2PO4, 0.4 mM KH2PO4, 4.2 mM NaHCO3, 0.7 mM MgSO4, 5.5 mM D-glucose and 10 mM HEPES) containing 5 µM of MitoSOX (stock prepared as 5 mM solution in DMSO) and incubated at 37 °C in the 5% CO2/air incubator for 10 min. Cellular ROS levels were measured by using the fluorescent probe DCFH-DA in Hank’s solution containing 10 µM of the fluorescent probe (stock prepared as 20 mM solution in DMSO) and incubated at 37 °C in the 5% CO2/air incubator for 40 min. Then, cells were washed with 0.2 mL of Hank’s solution three times and the fluorescence was measured in a fluorescence plate reader  with incubation at 37 °C. Filters were Ex = 510 ± 10 nm, Em = 580 ± 10 nm for MitoSOX, and Ex = 510 ± 10 nm, Em = 540 ± 10 nm for DCFH-DA, and readings were performed from the bottom of the plate). As positive control for the technique we used rotenone, a specific inhibitor of mCx-I, for mitochondrial ROS levels, and H2O2 for cellular ROS levels.Mitochondrial and cellular ROS levels were measured by using fluorescent probes in 96 well black plates  as previously described . The celThe cell-permeant, cationic, red-orange fluorescent dye tetramethylrhodamine ethyl ester (TMRE) , which is rapidly sequestered by active mitochondria, was used to evaluate the mitochondrial transmembrane potential. Since dead cells become completely depolarized, we analyzed live-gated cells to detect the decrease in mitochondrial transmembrane potential, which is associated with apoptosis. Cells were incubated at 37 °C for 30 min in the presence of 40 nM TMRE. They were then harvested after washing with PBS, and analyzed by flow cytometry . The mean fluorescence of untreated cells was set at 100%. CCCP (carbonyl cyanide m-chlorophenyl hydrazone), a mitochondrial oxidative phosphorylation uncoupler, was used as a positive control at a concentration of 20 μM during 30 min.One-way ANOVA and Tukey’s test were applied to calculate significant differences among samples (α = 0.05). All statistical analyses were performed with GraphPad Prism version 7.00 .Our study provides the first evidence of the expression of the H4R isoforms in human TCL, and demonstrates that this histamine receptor subtype is involved in histamine-mediated antitumor responses. In the different cell lines employed, the H4R ligands produced similar responses in terms of cell viability and apoptosis, which seemed to be independent of the profile of H4R isoforms expressed in each cell line. We hypothesize that the level of expression of the full length functional H4R isoform is enough to trigger the studied antitumoral responses. However, the precise role of the H4R isoforms in cell proliferation needs to be thoroughly explored.Histamine produces antitumor effects and improves the efficacy of panobinostat thus, this biogenic amine might represent an attractive compound to be used as a single therapy or in combination with HDACi for the treatment of these hematological malignancies.


The robust proliferation of cancer cells requires vastly elevated levels of protein synthesis, which relies on a steady supply of aminoacylated tRNAs. Delivery of tRNAs to the cytoplasm is a highly regulated process, but the machinery for tRNA nuclear export is not fully elucidated. In this study, using a live cell imaging strategy that visualizes nascent transcripts from a specific tRNA gene in yeast, we identified the nuclear basket proteins Mlp1 and Mlp2, two homologs of the human TPR protein, as regulators of tRNA export. TPR expression is significantly increased in lung cancer tissues and correlated with poor prognosis. Consistently, knockdown of TPR inhibits tRNA nuclear export, protein synthesis and cell growth in lung cancer cell lines. We further show that NXF1, a well-known mRNA nuclear export factor, associates with tRNAs and mediates their transport through nuclear pores. Collectively, our findings uncover a conserved mechanism that regulates nuclear export of tRNAs, which is a limiting step in protein synthesis in eukaryotes. Protein synthesis is a fundamental biological process for cells to grow and proliferate. Amino acids are the building blocks for proteins, and each is carried to ribosomes for protein synthesis by its own specific transport RNAs (tRNAs). An imbalanced or malfunctioning pool of cellular tRNAs may cause uncontrolled cell growth and proliferation, which are hallmarks of cancer. Nuclear pore complexes (NPCs) consist of multiple proteins termed nucleoporins that mediate transport of materials between the nucleus and the cytoplasm. Our previous study discovered that tRNA genes in yeast associate with NPCs to coordinate tRNA synthesis with nuclear export. Here, we develop a live cell imaging strategy to elucidate the machinery for tRNA nuclear export, and identify the nucleoporin TPR as a regulator of the process. We find that TPR is overexpressed in lung cancer tissues and correlated with poor prognosis, whereas down-regulation of TPR inhibits tRNA nuclear export, protein synthesis and cell growth. We further show that the nuclear export factor NXF1 associates with tRNAs and mediates their transport through NPCs. Our findings uncover a conserved mechanism by which NPCs control the quantity and quality of tRNAs before they reach the cytoplasm to execute their roles in protein synthesis. Once spliced from the tRNA in the cytoplasm  were spotted on different selective plates: YPDA , SC-leu [synthetic complete medium lacking leucine to select for the plasmid with tS(CGA)C-2×MS2bs::LEU2], YPDA+zeo [YPDA medium containing zeocin to select for Δts(cga)c::bler], YPDA+hygro (YPDA medium containing hygromycin to select for Δlos1::hphMX), and SC-his (synthetic complete medium lacking histidine to select for TDH3p-MS2CP-yeGFP::HIS3) plates. Tetrad H1 was saved as MRG 5789. Right panel: Fivefold serial dilutions of tetrads J4 [tS(CGA)C], G3 [tS(CGA)C + Δlos1], I3 [tS(CGA)C-2×MS2bs] and H1 [tS(CGA)C-2×MS2bs + Δlos1] were spotted on synthetic complete medium to compare their growth rate. tS(CGA)C-2×MS2bs provided the only source of the essential CGA-codon tRNA to the cell in I3 and H1, and their growth was largely unchanged. (B) A single 3′-DIG labeled LNA-modified oligonucleotide probe was used to detect pre-tRNASer(CGA)-2×MS2bs and mature tRNASer(CGA), as well as pre-tRNASer(CGA). An uncropped, 2-minute exposure is shown on the left. A 5-minute exposure of a second gel loaded with higher levels of RNA extracts is shown on the right. (C) A different oligonucleotide probe was used to detect both pre-tRNASer(CGA)-2×MS2bs (pre) and the spliced 2×MS2bs intron within the same sample preparations of (A) Meiotic segregation of markers among tetrads bearing (TIF)Click here for additional data file.S2 FigSer(CGA) with (+MS2bs) or without MS2 sites (-MS2bs). Nab2-mCherry shows the nuclei. Imaged were strains MRG5788 (wt), MRG5789 (Δlos1), MRG5817 , and their derivatives with either pJW031-LYS2[tS(CGA)C/LYS2/CEN] or pRJG1[YCplac111-Sb-tS(CGA)C-2×MS2bs::LEU2]. Scale bar = 10 μm.Representative images of cells expressing MS2-GFP and pre-tRNA(TIF)Click here for additional data file.S3 Fig(A) Disease summary for TPR from ONCOMINE. Cell color represented the best gene rank percentile for the analyses included in the cell. (B) TPR protein expression in the NCI-60 cell lines grouped according to their tissue origins. Data were obtained from NCI-60 proteome resource, which included a core cancer proteome of 5,578 proteins consistently quantified across various tissue types. (C) Left and Middle: TPR mRNA level in the NCI-60 cell lines grouped according to their tissue origins. Data were extracted from the GSE5720 (top row) and GSE5846 (bottom row) mRNA expression profiles of the NCI-60 cancer cell panel. 201730_s_at (left) and 201731_s_at (middle) were two different probes used to detect the mRNA level of TPR. Right: Correlation analysis of TPR protein abundance (from NCI-60 proteome resource) and mRNA level in NCI-60 cell lines.(TIF)Click here for additional data file.S4 Figt-test; *P < 0.05. (B) FACS profiles and quantifications of lung cancer cells. A549, H322, H460 and H1299 cells were treated with control (ctrl) or TPR siRNAs (Tsi-1 and Tsi-2), fixed with 70% ethanol and stained with PI before analyzed by FACS for ploidy. The vertical axis indicates cell number, while the horizontal axis is for DNA content. G1 and G2 phases are respectively represented as the first and second peaks starting from the vertical axis. S phase is marked as the intermediate striped domain. Each trial included at least 10,000 cells, and data  were analyzed by paired student’s t-test.(A) Quantification of the western blot results in control and TPR knockdown  A549, H322, H460 and H1299 cells. TPR / β-tubulin ratios  were analyzed by paired Student’s (TIF)Click here for additional data file.S5 FigGlu(CTC), tRNATyr(GTA), tRNAHis(GTG), tRNALeu(CAG), tRNAGly(CCC) and tRNAGly(GCC), using U6 as internal control. Relative nuclear enrichment of each tRNA was determined by its nuclear / total expression normalized to the same ratio of the tRNA within control. Data were presented as mean ± SD (n = 2).(A) Correlation analysis of relative abundance of tRNAs in Tsi and control cells. (B) Relative nuclear enrichment of tRNAs in H322 (top) and H1299 (bottom) cells. Nuclear and whole cell RNA extracts were prepared from control cells and cells with TPR knockdown . RT-qPCR was performed for each extract to measure the level of tRNA(TIF)Click here for additional data file.S6 FigGlu(CTC), tRNATyr(GTA), tRNAHis(GTG), tRNALeu(CAG), tRNAGly(CCC) and tRNAGly(GCC), using U6 as internal control. Data were normalized to the control and presented as mean ± SD (n ≥ 2). (B) Nascent pre-tRNA levels. Whole cell RNA extracts were prepared from control cells and cells with TPR knockdown . RT-qPCR was performed to measure the levels of nascently transcribed pre-tRNAArg(TCT), pre-tRNATyr(GTA) and pre-tRNALeu(CAA), using U6 as internal control. Data were normalized to the control and presented as mean ± SD (n = 2).(A) Total abundance of tRNAs. Whole cell RNA extracts were prepared from control cells and cells with TPR knockdown . RT-qPCR was performed to measure the total abundance of tRNA(TIF)Click here for additional data file.S7 Figt-test; *P < 0.05. (B) Quantification of colony formation assay done in control and NXF1 knockdown (Nsi-1 and Nsi-2) cells. Data  were analyzed by paired student’s t-test; **P < 0.01.(A) Nuclear enrichment of tRNAs in H322 (top), H460 (middle) and H1299 (bottom) cells without (control) and with NXF1 knockdown (Nsi-1 and Nsi-2). Relative nuclear enrichment of each tRNA tested was determined by its nuclear / total expression normalized to the same ratio of the tRNA within the control, shown as mean ± SD (n = 2), and analyzed by Student’s (TIF)Click here for additional data file.S8 Fig(A) NXF1 mRNA level in human lung cancer (T) and adjacent non-tumor (N) tissues. Data were extracted from GSE7670, GSE10072 and GSE31210, normalized to the median value of the non-tumor tissues in each dataset, and compiled for analysis. (B) Left: Western blot to detect the expression of NXF1 in paired tumor (T) and adjacent non-tumor (N) tissues from lung cancer patients. β-tubulin served as the loading control. Right: Quantification of NXF1 expression relative to β-tubulin in paired tumor (T) and adjacent non-tumor (N) tissues from lung cancer patients. (C) Western blot to detect the expression of NXF1 in control and TPR knockdown  A549, H322, H460 and H1299 cells. β-tubulin was used as the loading control.(TIF)Click here for additional data file.S9 FigPro (C top) and tRNASer (C bottom) isoacceptors in control (ctrl) and TPR knockdown (Tsi) A549 cells to codon usage of the top 10 up-regulated (Up) and the 10 most down-regulated (Down) genes in lung cancer tissues with high TPR expression. Cytoplasmic abundance of tRNA was calculated as tRNAcyt = tRNAtot - tRNAnuc, using the data from the tRNA PCR array.(A) Western blot to detect the phosphorylation of eIF2α. Protein extracts were prepared from H322 and H460 cells without (control) or with TPR knockdown . Numbers indicate the ratios of TPR / β-tubulin (top) and p-eIF2α / eIF2α (bottom). (B-C) Correlation of cytoplasmic abundance of different tRNA species (B), tRNA(TIF)Click here for additional data file.S10 Fig(A) Measurement of nuclear RNA enrichment. Nuclear and whole cell RNA extracts were prepared from A549 cells (control) and A549 cells with TPR knockdown . RT-qPCR was performed for each extract to measure the level of U1 snRNA, GAPDH mRNA and 5.8S rRNA, using U6 as an internal control. Relative nuclear enrichment of each RNA was determined by its nuclear / total expression normalized to the ratio within the control. Data were presented as mean ± SD (n = 2). (B) Total abundance of other RNAs. Whole cell RNA extracts were prepared from control cells and cells with TPR knockdown . RT-qPCR was performed to measure the total abundance of U1 snRNA, GAPDH mRNA and 5.8S rRNA, using U6 as internal control. Data were normalized to the control and presented as mean ± SD (n = 2).(TIF)Click here for additional data file.S11 FigWestern blot to detect the expression of TPR, XPO1, NXF1 and NUP62 in A549 cells transfected with TPR-specific siRNAs (Tsi-1 and Tsi-2) or a control siRNA.(TIF)Click here for additional data file.S1 Text(A) Yeast strains. (B) Oligonucleotides. (C) TPR mRNA level in the NCI-60 cell lines from GSE5720. (D) TPR mRNA level in the NCI-60 cell lines from GSE5846. (E) TPR protein abundance in cell lines from the NCI-60 proteome resource. (F) Correlation analysis of TPR mRNA level and clinicopathological features in lung cancer patients.(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S2 Data(XLSX)Click here for additional data file.


Vibrio cholerae is the causative agent of the diarrhoeal disease cholera and is responsible for seven recorded pandemics. Several factors are postulated to have led to the decline of 6th pandemic classical strains and the rise of El Tor biotype V. cholerae, establishing the current 7th pandemic. We investigated the ability of classical V. cholerae of the 2nd and 6th pandemics to engage their type six secretion system (T6SS) in microbial competition against non-pandemic and 7th pandemic strains. We report that classical V. cholerae underwent sequential mutations in T6SS genetic determinants that initially exposed 2nd pandemic strains to microbial attack by non-pandemic strains and subsequently caused 6th pandemic strains to become vulnerable to El Tor biotype V. cholerae intraspecific competition. The chronology of these T6SS-debilitating mutations agrees with the decline of 6th pandemic classical strains and the emergence of 7th pandemic El Tor V. cholerae.The gram-negative bacterium  Vibrio cholerae has caused seven recorded cholera pandemics. The factors responsible for the decline of 6th pandemic classical biotype strains are not well understood. Here, Kostiuk et al. propose that classical strains underwent sequential mutations in type-six secretion system genes that disadvantaged them when confronted with 7th pandemic El Tor biotype strains.The bacterium  Vibrio cholerae is a gram-negative bacterium and the causative agent of the diarrhoeal disease cholera. Throughout modern history, seven cholera pandemics have been reported, all caused by pandemic strains of the O1 serogroup. Understanding how these O1 pandemic strains evolved is hampered by the absence of available strains. Historical strains were not isolated until the germ theory became accepted in the late 1800s. Furthermore, V. cholerae colonises soft tissues and is noninvasive. Therefore, historical specimens for DNA extraction are rare. As a result, DNA sequences are available principally from the 6th pandemic  and the ongoing 7th pandemic . A preserved intestine from an 1849 cholera victim belonging to the Mütter Museum collection in Philadelphia offers unprecedented insights into 2nd pandemic V. cholerae 2.2. Contraction of the T6SS outer sheath ejects an inner tube consisting of polymerised Hcp proteins, capped with effector proteins, into adjacent bacteria. These effectors are toxic unless inhibited by cognate immunity proteins in the attacked bacterium. Three distinct genetic loci across two chromosomes encode the T6SS in V. cholerae: auxiliary cluster 1, auxiliary cluster 2 and a large cluster, each harbouring an effector-immunity pair: tseL & tsiV1, vasX & tsiV2 and vgrG3 & tsiV3, respectively. Effector and immunity pairs must have evolved in tandem with a cognate immunity protein for each effector. Each immunity protein protects only against a single cognate effector because cross-resistance has not been observed3.The T6SS is a bacterial nanomachine embedded in the envelope of gram-negative bacteria that mediates contact-dependent translocation of effector toxins into neighbouring cells3. Compatibility groups were named as follows: the first A refers to TsiV1 (Axx), the second A to TsiV2 (xAx) and the third A to TsiV3 (xxA). Divergent alleles at each locus were named in the order of discovery  for the auxiliary 1, 2 or large cluster, respectively, giving rise to 27 currently known compatibility groups in V. cholerae3. Compatibility groups were further classified into subfamilies to account for distinct TsiV1 amino acid sequences among the same modules: the 6th pandemic classical strains are represented by compatibility groups A1A1A1 (e.g. strain NIH41), A2A1A1 (e.g. strains CA401 and O395) and A3A1A1 (MZO-2); A4A1A1 (e.g. strain A59) was identified in this study. Members of the same compatibility group are immune to or compatible with each other3, as homologous immunity proteins define compatibility groups. In contrast, V. cholerae strains that do not encode the same effector and immunity genes will compete and are considered to be incompatible. Pandemic strains are subdivided into two biotypes; the seventh pandemic V. cholerae O1 El Tor biotype and the sixth pandemic O1 classical biotype, which evolved as distinct lineages8. The causes that led the 7th pandemic El Tors to replace classical strains as the source of pandemic cholera remains an intense research area. Three main hypotheses support classical biotype displacement: distinct virulence gene regulation, additional virulence factors encoded by El Tor V. cholerae, and biotype-specific phenotypic differences11. For example, El Tor and classical strains regulate ~1 in 8 genes differently, resulting in biotype-specific spatial-temporal expression of the main virulence factors, cholera toxin (CT) and toxin-coregulated pilus (TCP)10.Based on the similarity of TsiV1, TsiV2 and TsiV3 at each locus in 6th and 7th pandemic strains, we initially classified all 6th pandemic strains into the same compatibility group as the AAA-7th pandemic strainsVibrio cholerae strains, including the Vibrio seventh pandemic island 1 (VSP-I) and 2 (VSP-II), HlyA, PilE, MSHA and RTX. Phenotypically, the El Tor biotype displays increased biofilm production and motility compared to classical strains11. Lastly, lytic phages are specific to either of the two biotypes, inviting the hypothesis that phage population fluctuations could have contributed to the biotype replacement13. El Tor strains cause a less virulent form of cholera accompanied by a more extended period of bacterial shedding16, likely due to the considerable differences between the biotypes described above, thereby benefiting the pathogen by increasing dissemination time16.Numerous additional virulence factors encoded within El Tor genomes are either absent or differentially regulated in classical V. cholerae to improve understanding of how bacterial competition plays in cholera’s pathogenesis. In this work, we examined three aspects of competitiveness across pandemic cholera strains: the ability to engage in T6SS battle with commensal bacteria, compete with non-pandemic strains and compete with other pandemic strains.We investigated differences in the DNA sequences encoding T6SS genes of classical and El Tor biotype 1. Because the sequencing effort was not designed to provide sufficient sequencing depth to cover the entire T6SS gene clusters, we designed specific booster probes for the enrichment and adequate coverage of these loci. Re-sequencing the microbial content from the same Mütter Museum specimen provided an average coverage depth of ~300x across the T6SS gene clusters  revealed frameshift mutations in the large gene cluster17. Therefore, we conducted a comparative analysis of the re-sequenced T6SS clusters from the 2nd pandemic strain PA1849 and the 6th pandemic classical strain O395. T6SS sequences from each genome were aligned with those of the El Tor reference strain C6706. The 2nd and the 6th classical pandemic strains PA1849, and O395 encode a 12-nucleotide deletion (Δ293-304) in VCA0109 renamed vasN. In addition, the 6th pandemic classical strain O395 harbours an 8-nucleotide frameshift mutation (Δ514-521) in the structural gene vasK (VCA0120), one single-nucleotide polymorphism (SNP) in the effector tseL, and another SNP in its cognate immunity gene tsiV1  and vasE (VCA0114) genes are shared among all 6th pandemic strains  links the outer membrane protein TssJ with the inner membrane protein TssL, forming the membrane core complex of the T6SS19. Deletions of vipA, vasE or vasK in strain V52, which constitutively expresses the T6SS, abolish Hcp secretion  and abrogate T6SS-mediated killing20. Therefore, the mutations highlighted in Fig. vasN in-frame deletion removes four amino acids in VasN, a structural protein essential for Hcp secretion and T6SS function in general20.VipA–VipB complexes constitute the contractile outer sheath of the T6SSV. cholerae strain V52 with an El Tor T6SS . This experiment allowed us to determine whether the mutations found in classical strains interfere with T6SS activity while bypassing potential strain-specific regulatory differences21. Streptomycin-resistant V. cholerae V52 with the vasKΔ514-521 allele from the 6th pandemic classical strains or with the vasNΔ293-304 allele from 2nd and 6th pandemic classical strains were incubated with rifampicin-resistant E. coli (see ‘Methods’ for details). The vasKΔ514-521 and the vasNΔ293-304 V52 strains lost T6SS activity and did not kill E. coli comparably to the ΔvasK mutant control  in 6th pandemic strains.Taken together, these results suggest that the deletion in V. cholerae strains encoding the same T6SS effector and immunity alleles, rendering them immune to reciprocal T6SS-mediated attack and permitting coexistence3. Comparative sequence analysis of compatibility groups revealed that TsiV2 and TsiV3 of 6th pandemic strains are identical to their counterparts in C6706  are immune to each other was experimentally determined next. To test the ability of 6th pandemic V. cholerae to coexist with other strains of the AAA compatibility family, O395 (A2A1A1), CA401 (A2A1A1) and NIH41 (A1A1A1) were competed against strain V52 (A1A1A1) or V52∆vasK  survived exposure to V52 or V52∆vasK resulting in a competitive index of ~1. The competitive index of incompatible AM-19226 (C1D4F1) that survive exposure to V52 was ~104-fold lower, and the competitive index of AM-19226 surviving exposure to V52∆vasK was ~103-fold higher  but different subfamilies  or tsiV1163Ile (A1) allele to further evaluate the phenotype of this amino acid substitution. The CA401 strain harbouring the tsiV1163Ile allele was fully protected from the V52 T6SS, while CA401 expressing the tsiV1163Phe allele experienced a significant reduction in viability analogous to the CA401 WT allele (TsiV1163Phe = A2)  Fig. . Deletinted Fig. . WesternV. cholerae belonging to distinct T6SS compatibility groups compete against each other. Those of the AAA genotype are predominately human pathogens that outcompete all other non-AAA strains tested thus far3. We hypothesised that 6th pandemic classical strains would be outcompeted by non-AAA strains because of the T6SS disabling deletions in vasNΔ293-304 and vasKΔ514-521 —regardless of their tsiV1 allele as long the non-AAA strain does not represent an Axx compatibility group (e.g. groups AAB (strain MZO-2) or group ABK (strain YB2A12). Classical 6th pandemic V. cholerae were competed against non-AAA environmental isolates DL4211 (CEE), DL4215 (CEC), V51 (CDA) or 1587 (CDC) at a 1:1 ratio. Non-AAA strains outcompeted CA401 and NIH41 between 103 and 104 fold compared to controls  harboured the additional two nucleotide insertion in vasE and one nucleotide insertion in vipA  V. cholerae , thereby increasing chances for survival in select interspecific encounters34.The disadvantages of lacking T6SS activity include the inability to battle intra- and interspecific competitors and, consequently, the decreased uptake of exogenous DNAV. cholerae   at 37 °C shaking or on LB agar plates (supplemented with 1.5% agar). Bacteria were grown in the presence of 100 µg/mL ampicillin, 100 μg/mL streptomycin or 50 µg/mL rifampicin. The strains used in this study are described in Table tsiV1 was constructed as described previously using pWM91-based knockout constructs35. Knock-in versions of PA1849 alleles of vasK and vasN were made using the same approach. Table The in-frame deletion mutant CA401∆21. Briefly, two V. cholerae strains or a V. cholerae strain and E. coli MG1655 were mixed at indicated ratios and incubated on pre-dried LB agar plates. After a 4 h incubation at 37 °C, bacteria were harvested, serially diluted and plated onto LB agar plates supplemented with selective antibiotics to enumerate surviving V. cholerae or E. coli bacteria. The next day, colony-forming units (CFUs) were counted.Competition assays were performed as described previously600 to 1.0. Cell pellets from mid-logarithmic growth phase bacterial cultures were resuspended in PBS/2X lysis buffer, boiled and centrifuged. Supernatants were loaded and electrophoresed in either 12% or 15% acrylamide SDS-PAGE at 120 V before transfer to nitrocellulose. After blocking in dry milk/1X TBST for 1 h, blots were probed with primary antibodies diluted to 1:5000 (anti-FLAG), 1:500 (anti-Hcp) or 1:10,000 (anti-DnaK) followed by probing with fluorescently labelled secondary antibodies diluted at 1:10,000. Images were captured with a LICOR Odyssey scanner and analysed using Image Studio Lite software . The resulting relative quantification (RQ) values of all samples were normalised against expression of strain C6706.RNA from bacterial cultures grown to the mid-logarithmic phase of growth was extracted using TRIzol reagent (Invitrogen), treated with DNase I (Invitrogen) and transcribed into cDNA using the SuperScript III Reverse Transcriptase (Invitrogen). Quantitative real-time PCR (qPCR) was performed with the SensiFAST SYBR No-ROX Kit (FroggaBio) using the CFX96 Real-Time System (Biorad). Thermocycling parameters were as follows: 95 °C for 2 min hot start, 40 cycles at 95 °C for 15 s, and 60 °C for 1 min followed by a melting curve. Primers to genes of interest were designed using PrimerQuest software from Integrated DNA Technologies (IDT). Primers were tested for performance in qPCR with a cDNA concentration gradient, and those with slopes between −3.3 and −3.7, the efficiency of ∼1.0 and We analysed tissue collected from a single intestinal sample (specimen 3090.13) taken from a cholera patient in Philadelphia in 1849 and archived by the Mütter Museum in Philadelphia, PA, USA. The Mütter Museum approved sampling and analysing this sample. All tissue handling and library preparation (before indexing amplification) were performed in a positive-pressurised ancient DNA-appropriate laboratory at Arbor Biosciences in which no human or cholera tissue handling or library preparation had previously been performed. We employed field-appropriate standards of anti-contamination technique, including the use of full-body suits, frequent bleach-based work surface and tool decontamination, and blank extraction reactions containing only reagents without template.Two 5 × 5 mm squares  was taken to library preparation and indexing amplification using the Swift Biosciences (Ann Arbor Michigan) Accel-NGS(R) Methyl-Seq DNA Library Kit following the manufacturer’s standard procedure. The library was index-amplified 10 cycles using dual 8 bp-indexing primers.V. cholerae O395 genome reference chromosomes (NCBI Accessions NC_009456 and NC_009457) following soft-masking regions annotated as repeat elements. Where probes overlapped regions of known SNPs in PA1849, probes containing those SNPs were also included (n = 203). Any probe candidate that overlapped 20 nt or more with annotated repeat regions, or that had multiple strong hybrid sites in the genome were eliminated from the design. This resulted in a final set of 186,228 probes. A similar procedure was used for the T6SS probe set, starting with the V. cholerae T6SS auxiliary 1, auxiliary 2 and large loci as references for probe design, and probes for putative PA1849 SNPs included as well (n = 2). This final set comprised 2876 probes.Two distinct probe sets were designed for this project, one designed to enrich the entire cholera genome, and another targeting only the three T6SS clusters. The whole-genome kit tiled 80 nt probes every 20 nt across both Target enrichment used a combination of whole-genome and T6SS probes at a mass ratio of 99% whole-genome, 1% T6SS or exclusively T6SS probes. Depending on library availability, between 75 and 1000 ng of sample, or 2 and 500 ng of extraction blank library, were taken to enrichment using the myBaits protocol version 3.0. This involved a first round of overnight hybridisation at 60 °C and a single Wash Buffer 2 hot wash, followed by post-capture amplification of 80% of the resulting volume of bead-bound enriched libraries for 14 cycles prior to purification. Then the enriched libraries were taken to a second round of enrichment using identical conditions as the first, except three washes were used during cleanup. Half of the available volume of bead-bound library was taken to 8 cycles of amplification prior to purification. These double-enriched libraries were then submitted for sequencing. Enriched and non-enriched versions of each library were then sequenced using PE100 protocol on a HiSeq 2500 lane, demultiplexed by dual 8 bp barcodes.The following analyses were performed on sequencing reads produced with (SL264753) and without (SL264742) target enrichment. Enriched sequencing reads (SL264753) were used to generate consensus sequences and identify variant loci due to significantly increase coverage over the T6SS clusters.37. Merged reads were aligned to a reference FASTA with the Burrows-Wheeler Aligner (bwa v0.7.17) MEM algorithm38. For analysis of the T6SS loci, reference FASTA files were constructed by concatenating genomic islands extracted from C6706 (PacBio sequence of laboratory stock) or O395 (PacBio sequence of laboratory stock) with 100 nucleotide spacers between each region. For phylogenetic analysis, reads were mapped to the whole-O395-genome. SAM files produced were then sorted and marked for duplicates with Picard Tools (v2.17.11) to generate sorted, unique BAM files, which were indexed with Picard Tools39. Variants were called against the constructed reference FASTA, and consensus sequences were generated with Pilon (v1.22)40. For analysis of the T6SS loci, PA1849 consensus sequences were aligned to C6706 and O395 reference sequences using the progressive MAUVE algorithm (v1.1.1) algorithm in Geneious (v2019.0.4), assuming colinear genomes. Genome coverage plots were generated from sorted, unique BAM files uploaded to the Integrative Genomics Viewer (v2.9.4).Raw PA1849 FASTQ files were QC validated with FastQC (v0.11.9) to assess Phred quality score and nucleotide distribution over reads. The forward adapter (AGATCGGAAGAGCACACGTCTGAACTCCAGTCA) and the reverse adapter (AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT) were removed from paired-end read files, and ends were trimmed with a Phred quality score cut-off of 30 using cutadapt (v1.16). Reads below a minimum length cut-off of 30 nucleotides were removed. Overlapping paired-end reads from the trimmed FASTQ files were merged into single-end reads with NGmerge (v0.2)1, because of a difference in Illumina chemistry, lack of sonication of the tissue and enrichment with our updated T6SS probes. Nucleotide substitution patterns characteristic of ancient DNA samples  were not observed for these samples. A low frequency of C > T substitutions can be seen at either end of the mapped reads 43 with a minimum blastp percentage identity of 95% for calling core genes. Roary extracted and aligned 688 core genes . The core-genome alignment was reduced to only loci harbouring polymorphisms using SNP sites (v2.4.1)44. A total of 6,225 distinct SNP sites were extracted from the 688 core genes. A Maximum Likelihood phylogenetic tree was built using the RAxML (v8.2.12) GTR model. Model was selected using jModelTest (v0.1.6)45. Statistical branch support was obtained from 100 bootstrap repeats. Phylogenetic trees were visualised from RAxML-generated newick files using TreeGraph 2 (v2.15.0-887 beta)46. Branches with bootstrapping support values <70 were collapsed. Alignments of amino acid sequences were performed with MUSCLE (v3.8.425)47 and alignments of the nucleotide sequences of whole-gene clusters were performed using the progressive MAUVE algorithm48 in Geneious (Geneious Prime v2019.0.4). To display the diversity of amino acid sequences as a radial tree, aligned sequences were analysed using RAxML 49 and displayed with Geneious Prime (v2019.0.4). Some genomes were poorly assembled over the T6SS clusters, and thus corresponding read files from SRA (Table Core-genome-based phylogenetic trees were constructed as follows: Genomic FASTA files for tree building were obtained from the PATRIC database or NCBI Table  and annoFurther information on research design is available in the Supplementary information.Reporting summary.


Rationale: Triple-negative breast cancer (TNBC) is characterized by its unique molecular profile, aggressive nature and lack of targeted therapy. Chemotherapy induces expression of pluripotency factors and mediates an active induction of breast cancer stem cells (BCSCs) in TNBC, which potentiates the risk of tumor recurrence and metastasis and increases patient mortality. Adenosine receptor 2B (A2BR) expression and activation of its downstream signaling pathway has been implied to promote breast cancer metastasis. This study is to investigate the role of A2BR in the regulation of chemotherapy-induced BCSC enrichment.Methods: We generated shRNA-mediated A2BR knockdown subclones in TNBC cell lines and evaluated the effect on the BCSC phenotype by Aldefluor and mammosphere assays in vitro. We performed chromatin immunoprecipitation (ChIP) assay to investigate recruitment of transcription factor FOXO3 and histone modification enzymes KDM6A and p300 to the regulatory regions of pluripotency factors, as well as levels of histone modification marks H3K27ac and H3K27me3 on these regions. We employed both xenograft model and genetically engineered, autochthonous breast cancer model to evaluate the effect of A2BR on chemotherapy-induced BCSC enrichment in vivo.Results: We demonstrated that chemotherapy increased protein level of A2BR, which contributed to chemotherapy-induced pluripotency factor expression and BCSC enrichment in TNBC. A2BR mediated activation of p38 MAPK and nuclear translocation of chromatin remodeling factor SMARCD3, which interacted and recruited histone demethylase KDM6A and histone acetyltransferase p300 specifically to the pluripotency factor genes NANOG, SOX2 and KLF4. Recruitment of KDM6A and p300 decreased histone H3K27me3 and increases H3K27ac marks, and increased transcription factor FOXO3 binding to NANOG, SOX2 and KLF4 genes, leading to transcriptional activation of these genes and BCSC specification. Genetic or pharmacological inhibition of A2BR blocked chemotherapy-mediated epigenetic activation of pluripotency factor genes and BCSC enrichment in vitro and in vivo, and delayed tumor recurrence after chemotherapy was discontinued.Conclusion: Chemotherapy-induced A2BR expression mediates epigenetic activation of pluripotency factors and promotes breast cancer stemness. Targeting A2BR in combination with chemotherapy may block BCSC enrichment and improve outcome in TNBC. Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) 50) Breast cancer stem cells (BCSCs) are a small and dynamic subpopulation of breast cancer cells that play a critical role in cancer metastasis A major mechanism underlying chemotherapy-induced BCSC enrichment is the increased expression of pluripotency factors NANOG, SOX2, OCT4, and KLF4 in response to chemotherapy The expression of pluripotency factors in cancer stem cells has been reported to be regulated at transcriptional level by different transcription factors in addition to themselves, including STAT3, HIF-1, GLI1, AR, and FOXO3 ADORA2B gene) expression and activation of its downstream signaling pathway has been shown to promote breast cancer metastasis NANOG, SOX2, and KLF4 genes. Reciprocal modification of H3K27me3 and H3K27ac marks increases transcription factor FOXO3 binding and transcriptional activation of pluripotency factor genes, leading to BCSC specification.Accumulation of extracellular adenosine, sequentially converted from extracellular ATP by CD39 and CD73 during tumor growth BRAF, CDKN2A, KRAS, and TP53 mutation), SUM149 , and SUM159 (anaplastic carcinoma cell line with PIK3CA and TP53 mutation) with Food and Drug Administration (FDA)-approved chemotherapy drugs paclitaxel and carboplatin for 72 h at the IC50 of the drug, and found that each of these chemotherapeutic drugs increased A2BR protein levels in all these cell lines   or A2BR knockdown subclones of MDA-MB-231 Figure A cells, ) Figure B, and in) Figure C. A2BR ks Figure B-C. Phars Figure D-E, indis Figure F and pro6 MDA-MB-231 NTC or A2BR knockdown subclone cells into the MFP of SCID mice, and when the tumor volume reached 200 mm3, the mice were treated with 10 mg/kg of paclitaxel by intraperitoneal injection every 5 days for three doses. Tumors were harvested for ALDH, mammosphere, and qPCR assays 3 days after the last dose. A2BR knockdown did not affect tumor growth rate or sensitivity to paclitaxel , protein kinase C-α (PKCα), PKCδ, AKT, and p38 MAPK pathways 1 Figure B, which 1 Figure A.+  database and compared A2BR expression pattern in different subtypes of breast cancer. A2BR expression is significantly higher in TNBC compared with ER/PRr Figure A, highlir Figure B, with ar Figure C. To invr Figure D and ther Figure E. Becausr Figure F. Taken NANOG, SOX2, and KLF4 genes and decreases H3K27me3 and increases H3K27ac marks of these sites, leading to increased chromatin accessibility, increased FOXO3 binding, and transcriptional activation of these genes, and finally BCSC specification , although nuclear SMARCD3 protein level increases in response to chemotherapy treatment. A caveat of this study is that the mechanism of the specificity has not been determined. It is important to elucidate SMARCD3 binding sites at genome-wide level and to determine genes that are regulated by SMARCD3 in response to chemotherapy treatment. A ChIP-sequencing experiment is warranted to determine whether SMARCD3 is recruited to specific genes or whether SMARCD3 is recruited to chromatin globally but only interact with histone modification enzymes at specific sites. In addition, our present study demonstrated the interaction of FOXO3 with KDM6A and p300 . All chemicals are listed in MDA-MB-231 cells were maintained in DMEM; SUM159 and SUM149 cells were maintained in DMEM/F12 (50:50), both of which were supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. Cells were maintained at 37°C in a 5% COpLKO.1-puro lentiviral vectors encoding shRNA targeting A2BR and SMARCD3 were purchased from Sigma-Aldrich, and the clone IDs are shown in Cultured cells were lysed in RIPA buffer (EMD Millipore), whereas tumor tissues were lysed in RIPA buffer and homogenized with an electric homogenizer. Proteins (50 μg) were separated by SDS-PAGE, blotted onto nitrocellulose membranes, and probed with primary antibodies . The memt) as 2-Δ(ΔCt), in which ΔCt = Ct (target) - Ct (18S rRNA), and Δ(ΔCt) = ΔCt (test sample) - ΔCt (control sample). Primer sequences (5' to 3') for RT-qPCR are shown in Total RNA was extracted with TRIzol (Invitrogen), precipitated with isopropanol, and treated with DNase . cDNA was synthesized with cDNA reverse transcription kit (Applied Biosystems) from 1 μg total RNA and qPCR analysis was performed using SYBR Green and the CFX96 Touch real-time PCR detection system (Bio-Rad). The expression of each target mRNA relative to 18S rRNA was calculated based on the cycle threshold  with protease inhibitor mixture (Roche) on ice for 10 min and centrifuged at 4°C at 3000 rpm for 10 min. The supernatants were saved as cytoplasmic fraction. Pellets were resuspended in high salt cell extraction buffer  with protease inhibitor mixture, homogenized with 30 full strokes in Dounce homogenizer, incubated on ice for 30 min, and centrifuged at 15,000 rpm for 30 min at 4°C. Supernatants were saved as nuclear fraction.Cultured cells were resuspended in hypotonic buffer  were incubated with control IgG or antibodies against FOXO3  or SMARCD3  in the presence of protein G-Sepharose beads (Amersham Biosciences) at 4 °C overnight, and the resulting immunoprecipitates were then subjected to immunoblot assays.5 cells were suspended in assay buffer containing 0.5 μM BODIPY-animoacetaldehyde and incubated at 37°C for 45 minutes. An aliquot of cells from each sample was treated with 50 mM diethylaminobenzaldehyde, an ALDH inhibitor, as a negative control for gating. Samples were analyzed by flow cytometry using FACScalibur (BD Biosciences).The ALDH assay was performed according to manufacturer's instructions . Cultured cells were trypsinized, whereas tumor tissues were minced, digested with 1 mg/mL of type 1 collagenase (Sigma-Aldrich) at 37°C for 30 min, and filtered through a 70-μm cell strainer. 5 x 10Cultured cells were trypsinized, whereas tumor tissues were minced, digested with 1 mg/mL of type 1 collagenase (Sigma-Aldrich) at 37 °C for 30 min, and filtered through a 70-μm cell strainer. The number of live cells was determined using trypan blue staining and single cell suspensions were seeded in six-well ultra-low-attachment plates (Corning) at a density of 5,000 cells/mL in complete MammoCult Medium (Stem Cell Technologies). Mammosphere cultures were photographed 7 days later using a phase contrast microscope (Olympus) and mammospheres ≥ 50 μm in diameter were counted using ImageJ software (NIH).Cultured cells or minced tumor tissues were cross-linked in 3.7% formaldehyde for 15 minutes, quenched in 0.125 mol/L glycine for 5 minutes and lysed with SDS lysis buffer. Chromatin was sheared by sonication, sonicated lysates were precleared with salmon sperm DNA/protein A agarose slurry (EMD Millipore) for 1 hour and incubated with antibodies  in the p6 MDA-MB-231 parental or knockdown subclone cells were injected into the MFP of 5-to-7 week-old female mice in a 1:1 suspension of Matrigel (BD Biosciences) in PBS. Mice were treated with drugs as indicated. For assays with MMTV-PyMT transgenic mice, mice were treated when the accumulated volume of mammary tumors in each mouse reached 150 mm3. Primary tumors were measured for length (L) and width (W), and tumor volume (V) was calculated as V = L × W2 × 0.524. Paclitaxel, carboplatin, and alloxazine were given by intraperitoneal injection; LY2228820 was given by oral gavage.Animal protocols were approved by Institutional Animal Care and Use Committee of West China hospital, Sichuan University and were in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals. For assays with SCID mice, 2 × 10Expression data for A2BR, NANOG, SOX2, OCT4, KLF4, and BCSC signature-gene mRNAs in different subtypes of primary breast cancers were accessed from The Cancer Genome Atlas (TCGA) invasive carcinoma gene expression dataset (cancergenome.nih.gov). Pearson test was performed to analyze the correlation of A2BR expression with the BCSC signature and OSNK signature in 123 TNBC patients. Kaplan-Meier curves were generated from a dataset containing gene expression and survival data from 3,951 breast cancer patients t test, whereas differences between multiple groups were analyzed by ANOVA with post hoc test. For all analyses, values of p < 0.05 were considered significant.All data are expressed as mean ± SEM. Differences between 2 groups were analyzed by 2-tailed Student's Supplementary figures and tables.Click here for additional data file.


Sites of live poultry trade and marketing are hot spots for avian influenza virus (AIV) transmission. We conducted active surveillance at a local live poultry market (LPM) in northern Vietnamese provinces in December 2016. Feces samples from the market were collected and tested for AIV. A new reassorted AIV strain was isolated from female chickens, named A/chicken/Vietnam/AI-1606/2016 (H5N6), and was found to belong to group C of clade 2.3.4.4 H5N6 highly pathogenic (HP) AIVs. The neuraminidase gene belongs to the reassortant B type. The viral genome also contained polymerase basic 2 and polymerase acidic, which were most closely related to domestic-duck-origin low pathogenic AIVs in Japan (H3N8) and Mongolia (H4N6). The other six genes were most closely related to poultry-origin H5N6 HP AIVs in Vietnam and had over 97% sequence identity with human AIV isolate A/Guangzhou/39715/2014 (H5N6). The new reassorted AIV isolate A/chicken/Vietnam/AI-1606/2016 (H5N6) identified in this study exemplifies AIVs reassortment and evolution through contact among wild birds, poultry farms, and LPMs. Therefore, active surveillance of AIVs is necessary to prevent potential threats to human and animal health.The online version contains supplementary material available at 10.1007/s00284-021-02661-z. Orthomyxoviridae. Among the AIV subtypes identified in wild aquatic birds based on two surface glycoproteins, hemagglutinin (HA1 to 16) and neuraminidase (NA1 to 9), H5Nx subtypes have been a major concern in the poultry industry and public health since the first highly pathogenic avian influenza virus (HPAIV) H5N1 subtype was detected in a goose in Guangdong (Gs/GD) province, China, 1996 [Avian influenza viruses (AIVs) belong to the family utinin HA to 16 anna, 1996 . Based ona, 1996 . Aquaticna, 1996 .In 2013, the first clade 2.3.4.4 H5N6 HPAIV was identified and was the result of a reassortant between the HPAIV H5N1 subtype and LPAIV H6N6, which circulate broadly in duck populations in southern and eastern China . OccasioIn Vietnam, the first Gs/GD lineage H5N1 HPAIV was detected in 2001 , and numLPMs are integral components of the poultry trade network in Vietnam. The behavior of poultry traders in Vietnamese markets is a potential risk factor for human and animal health, making it more likely for AIVs to overcome the species barrier . Hence, During the winter between 2016 and 2017, feces sampling in poultry was carried out at local LPMs and small-scale poultry farms in Ha Nam province, Vietnam (approximately 60 km from Hanoi to the south). A total 353 of fecal, tracheal, and cloacal swab samples were collected from four local live bird markets and poultry farms and plated into transportation medium  and stored at −80°C. Samples were then tested for AIVs using a matrix (M) gene-specific real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) method according to the WHO guideline for animal influenza virus detection , 19.For complete viral genome analysis of the new isolate, viral RNA was prepared from the allantoic fluid from the first egg passage using a QIAamp Viral RNA Mini Kit  following the manufacturer’s protocol. Viral genome amplification was performed using the conventional RT-PCR method with PrimeScript™ First-Strand cDNA Synthesis Kit and Premix Taq™  with universal primers previously described . The DNAPhylogenetic analysis based on each gene sequence was conducted using Molecular Evolutionary Genetics Analysis Version 7.0 software (MEGA 7.0). The evolutionary distances were computed using the Maximum Composite Likelihood method with 1000 replicates. Input nucleotide sequences included both the new isolate and reference sequences from the open access resources for the GenBank database of influenza virus. The length of eight segments containing the PB2, PB1, PA, HA, NP, NA, M, and NS genes used for phylogenetic analysis were 2280, 2274, 2151, 1704, 1497, 1380, 982, and 823 nucleotides, respectively.Gallus gallus) was the host of A/AI-1606/16 followed to COI and CHD partial genes analysis .Among the eight confirmed positive samples of influenza A virus by M-gene-specific RT-qPCR, we identified three of H5N1 and four of H9N2 avian influenza viruses (Supplementary Table 1). Interestingly, a fecal sample collected from a local LPM on December 30th, 2016 was suspected to be positive for HPAIV. In the first egg passage, the isolate showed signs of HPAI virus infection, such as death of the embryos and allantoic fluid in red at 36 h post-inoculation. The new reassortant strain of clade 2.3.4.4c H5N6 HPAIV was identified and named A/Chicken/Vietnam/AI-1606/2016 (abbreviated as A/AI-1606/16). The geographical location of the A/AI-1606/16 isolate was shown in Fig. Based on the genetic analysis, suggested that the A/AI-1606/16 isolate was closely related to domestic-poultry-origin AIVs. The six segments of PB1, HA, NP, NA, M, and NS genes were most closely related to the H5N6 HPAIV virus that circulated among domestic poultry in Vietnam between 2015 and 2016. The sequence similarity was greater than 99%. However, the PB2 gene was most closely related to A/duck/Mongolia/543/2015(H4N6), with 98.82% identity; and the PA gene was most closely related to A/duck/Hokkaido/20/2015 (H3N8), with 98.84% identity. The closest similarities of the eight gene segments of the A/AI-1606/16 virus are listed in Table In the phylogenetic tree analysis, the eight genes of the A/AI-1606/16 virus belonged to Eurasian lineages Fig. A–H. The The predicted amino acid sequence of the A/AI-1606/16 viral genome was analyzed to better understand the new isolate, and specific regions of the A/AI-1606/16 viral genome were examined  CHD gene identification; general banding patterns of 3 primer sets  in chicken kidney (control) and #1606 fecal sample for bird sexing , the female bird contains both W and Z chromosome as the result give to 2 single band , while the male bird contain only Z chromosome. (B) COI gene identification; bird species identification based on COI gene fragment (approximately 750bp in length). The PCR products were run on a 1.5% agarose gel at 135 volts for 30 mins (DOCX 629 kb)Below is the link to the electronic supplementary material.


FGA, FGB, FGG) genotypes. Constellations of fibrinogen, factor XIII A-subunit (F13A) and α2-antiplasmin (A2AP) genotypes predisposing for dense fibrin gels with high antifibrinolytic capacity  are related with reduced inflammation. As both relationships are likely to influence each other, we tested whether the association of fibrinogen genotypes with fibrinogen levels is influenced by F13A and A2AP genotypes in a population under proinflammatory stress. In total, 639 women were followed during pregnancy (2218 observations). The relationship between fibrinogen genotypes and levels was statistically assessed in univariate and multivariate analyses without and with stratification for F13A Val34Leu and A2AP Arg6Trp. Strong associations with fibrinogen levels could be found for FGB rs1800790G > A, FGA rs2070016T > C and FGG rs1049636T > C. For FGB rs1800790G > A and FGA rs2070016T > C, this relationship significantly depended on F13A Val34Leu and A2AP Arg6Trp genotypes. Specifically, in F13A 34Val/Val wildtypes, carriage of FGB rs1800790A was related to significantly lower fibrinogen levels compared with FGB rs1800790GG wildtypes (p < 0.01). For A2AP 6Arg/Arg wildtypes, a comparable relationship could be found (p < 0.04). As these genotype constellations related to lower fibrinogen levels have previously been shown to be associated with reduced inflammatory activity, these findings suggest that the influence of fibrinogen, F13A and A2AP genotypes on inflammation could affect the control of fibrinogen levels and vice versa.Fibrinogen synthesis is stimulated by proinflammatory triggers and depends on α-, β- and γ-fibrinogen ( FGA, FGB, FGG) and it is increased by acute-phase responses via interleukin 6 (IL6), glucocorticoids and others [FGB rs1800790G > A or a strongly linked genotype being consistently associated with higher fibrinogen levels [FGB rs1800790G > A and fibrinogen levels in steady-state situations [Expression of fibrinogen depends on gene loci of α-, β- and γ-fibrinogen  34Val/Val wildtype is a necessary precondition, and it is abrogated in carriers of the polymorphism F13A 34Leu allele [2-antiplasmin (A2AP) is necessary, which is highest in A2AP 6Arg/Arg wildtypes [F13A and A2AP genotypes and inflammation, which could be detected in different cohorts under proinflammatory stimulation [FGB rs1800790G > A minor allele(s)) were associated with reduced inflammatory activity if the presence of the F13A 34Val/Val wildtype gave the optimal background for highly crosslinked fibrin gels [A2AP 6Arg/Arg wildtype predisposed for a high antifibrinolytic capacity [Increasing fibrinogen concentrations are known to result in fibrin clots with increased density and high antifibrinolytic capacity . For thiu allele . For fulildtypes . Recentlmulation ,10. Carrcapacity ,12.F13A and A2AP genetics on inflammation are likely to influence each other, we tested in the present study the following hypothesis:As the association between fibrinogen genotypes and fibrinogen levels as well as the aforementioned influence of fibrinogen, FGB rs1800790G > A as well as polymorphisms of FGA and FGG) are related to reduced fibrinogen levels under proinflammatory stimulation, when F13A 34Val/Val wildtype and/or A2AP 6Arg/Arg wildtype is given.Fibrinogen genotypes known to be associated with higher fibrinogen levels at steady-state conditions  over the course of pregnancy. Pregnancy is known to be a proinflammatory condition with elevated biomarkers of inflammation ,14. FurtThe influence of genotype constellations potentially predisposing for dense fibrin clot structures and inflammatory activity on fibrinogen levels under proinflammatory stimulation was assessed in a cohort of 639 patients (2218 observations), followed during pregnancy because of history of fetal loss (FL), placental dysfunction (PD), pregnancy complications or venous thromboembolism (VTE). CRP and fibrinogen levels were determined regularly with each presentation. Data were analyzed anonymously.A2AP (Arg6Trp) rs2070863 (C > T), F13A Val34Leu (rs5985), FGA rs6050 (A > G), FGA rs2070016 (T > C), FGA rs2070006 (G > A), FGB −455G > A (rs1800790), FGB rs1800788 (C > T), and FGG rs1049636 (T > C) as well as CRP levels were characterized as described previously [Genotypes of 34Leu rs585, FGA rt-tests were performed and p-values were calculated. Multivariate analyses of fibrinogen levels were performed by logistic regression analysis adjusting for stage of pregnancy (trimester), age, primary diseases, and ethnicity. If indicated, these analyses were stratified for CRP elevation, F13A Val34Leu genotype or A2AP Arg6Trp genotype. To evaluate for potential interactive effects, corresponding interaction terms were included in logistic regression models (p for homogeneity) [For presentation of data distribution frequencies, mean standard deviation (SD), median and interquartile range (IQR) or cumulative probability plots were given, as indicated. For univariate analyses on fibrinogen levels, geneity) . StatistThe median age of patients included in the study was 32.1 years , and the following primary diagnoses were reasons for presentation in our hemostasis out-patient unit: history of miscarriage (38%), actual or history of placental dysfunction (21%), history of deep vein thrombosis (DVT) (14%), history of pulmonary embolism (PE) (3.8%). Patients presented regularly during pregnancy as well as 12 weeks postpartum. Until the end of the first, second, and third trimester, 277 (12.5%), 864 (39.0%), and 894 (40.3%) observations were available, respectively. Additionally, 183 (8.3%) observations until 12 weeks postpartum were included in the study.The distributions of clinical and laboratory data are summarized in Mean fibrinogen levels continuously increased with ongoing pregnancy . During the 12 weeks postpartum, a considerable decline in fibrinogen levels could be recognized (3.23 ± 0.81 mg/L). The frequency of CRP elevations ≥10 mg/L increased from 7.94% (first trimester) to 14.0% and 12.1% in the second and third trimesters, respectively. In the interval postpartum, only a small number of patients (2.7%) exhibited elevated CRP levels. For mean CRP levels, a comparable characteristic could be found .F13A, F13B and A2AP with fibrinogen levels. The findings are given in We tested the association of fibrinogen genotypes as well as of FGB rs1800790 A allele exhibited only a very small effect on fibrinogen concentration, carriage of the minor alleles of FGA rs2070016T > C or FGG rs1049636T > C influenced fibrinogen levels significantly. Interestingly, in our cohort, carriage of the minor alleles of FGB rs1800790G > A and FGA rs2070016T > C was related to lower fibrinogen levels compared with the corresponding wildtypes, and for FGG rs1049636T > C higher fibrinogen levels could be detected. For F13A Val34Leu, F13B His95Arg and A2AP Arg6Trp fibrinogen levels were equal for wildtypes and minor allele carriers.While carriage of the p < 0.0001; CRP <10 mg/L, 4.41 ± 1.10 mg/L, CRP ≥10 mg/L, 5.52 ± 1.23 mg/L, p < 0.0001). When considering inflammatory activity as measured by CRP elevation, a different behavior of the tested fibrinogen genotypes with respect to fibrinogen levels could be found , this genotype–phenotype relation tended to reverse. These findings could be confirmed in multivariate analyses adjusting for trimester, age, disease and ethnicity (data not shown).While for F13A 34Val/Val wildtype [FGB rs1800790 A-allele carriers could be found only in F13A 34Val/Val wildtypes, thus, F13A 34Val/Val wildtype seems to be a necessary precondition for this effect [F13A Val34Leu defined strata  was given. In carriers of F13A 34Leu this relation vanished. Heterogeneity for this effect between both F13A Val34Leu defined strata was statistically significant in univariate as well as in multivariate analyses . A similar tendency could be found for FGA rs2070016T > C. In F13A 34Val/Val wildtypes, carriage of the FGA rs2070016T > C minor allele was associated with lower fibrinogen levels compared with FGA rs2070016T > C wildtypes. In F13A 34Leu carriers, this effect of FGA rs2070016T > C genotype on fibrinogen levels was considerably diminished. Heterogeneity between both F13A Val34Leu strata was not statistically significant. For FGG rs1049636T > C, minor allele carriage was robustly associated with higher fibrinogen levels in both F13A Val34Leu strata.Considering F13A Val34Leu or A2AP Arg6Trp would have an influence on fibrinogen levels. Neither for F13A Val34Leu  nor for A2AP Arg6Trp  did fibrinogen levels differ significantly between wildtypes and minor allele carriers.We additionally evaluated whether A2AP Arg6Trp genotype influenced the relationship between fibrinogen genotype and level. This assumption was based on the facts that fibrin clots of A2AP 6Arg/Arg wildtypes are known to have a higher antifibrinolytic capacity [F13A Val34Leu. In individuals predisposed for a higher antifibrinolytic capacity (A2AP 6Arg/Arg wildtypes), carriage of the FGB rs1800790 A allele was related to lower fibrinogen levels. The same holds true for FGA rs2070016T > C. Here, the differences in fibrinogen levels were especially pronounced, and heterogeneity between both A2AP Arg6Trp defined strata was significant (p for homogeneity: 0.005). For FGG rs1049636T > C, again, carriage of the minor allele was robustly associated with higher fibrinogen levels in both A2AP Arg6Trp defined strata.We finally tested whether the capacity , and thacapacity . The resFGB, which has many different regulatory elements [FGB rs1800790G > A is a prominent example [FGB fragments carrying FGB rs1800790G > AG- and A alleles, respectively [FGB rs1800790G > AA alleles compared to those with the corresponding G alleles [FGB rs1800790G > A minor allele [FGB rs1800790G > A minor allele carriers when compared with FGB rs1800790G > A wildtypes [FGB rs4220G > A, which is in strong linkage disequilibrium with FGB rs1800790G > A, a significant interaction between inflammation, as measured by interleukin-6 levels and fibrinogen levels, has been described [The genetic background of fibrinogen synthesis is well-described, and different genetic polymorphisms of the fibrinogen gene loci have been shown to influence basal fibrinogen levels ,16. The  example ,18. Elecectively ,4. Furth alleles ,4. Meanwr allele ,6. Regarr allele . In thisr allele . Of noteildtypes . FinallyFGA rs2070016T > C, which has been evaluated in this study in more detail, different studies identified carriage of the minor allele to be associated with higher fibrinogen levels [FGG rs1049636T > C, data are more complex. Most investigations found lower fibrinogen levels in carriers of the corresponding minor allele [FGG rs1049636 C allele was associated with higher fibrinogen levels [For n levels ,22,23. Ir allele ,23. Howen levels . Moreoven levels ,26.Beside these polymorphisms located in fibrinogen gene loci, other loci were reported to be involved in genetic regulation of the strength of fibrinogen synthesis. These loci are involved in the regulation of inflammatory responses, with the loci of interleukin-6 receptor (IL6R) and interferon regulatory factor 1 (IRF1) being two examples ,22.Our analyses were performed on a cohort of pregnant women. Pregnancy is known to represent a proinflammatory trigger with elevated biomarkers of acute-phase response ,14. ThisFGB rs1800790 A-allele or FGA rs2070016 C-allele carriage was related to lower fibrinogen levels , FGB rs1800790G > A or FGA rs2070016T > C minor allele carriers exhibited significantly lower fibrinogen levels   .F13A and A2AP genetics, described previously [FGB rs1800790 A allele(s) or FGA rs2070016 C allele(s) is associated with significantly lower inflammatory activity, if F13A 34Val/Val wildtypes and/or A2AP 6Arg/Arg wildtypes are considered. This effect can be demonstrated for CRP levels in patients suffering from rheumatoid arthritis (RA) as well as patients with non-autoimmune inflammations (non-RA). In RA patients, clinical disease activity scores (disease activity score of 28 joints) indicate lower inflammatory activity in these constellations, as well [FGB rs1800790 A allele(s) or FGA rs2070016 C allele(s) exhibit higher basal fibrinogen levels [F13A 34Val/Val wildtype and/or A2AP 6Arg/Arg wildtype are also given, these situations with higher fibrinogen levels result in the generation of denser fibrin gels [As reflected by the hypotheses of our study, we think the findings are plausible when considering the interactive effects of fibrinogen, eviously ,10,11,27n levels ,18. In an levels . If F13Arin gels ,30. Hererin gels ,31, whicF13A and A2AP, which predispose for reduced inflammatory activity [In summary, we could demonstrate that genotype constellations of fibrinogen, activity ,10,11 aractivity ,33.F13A and A2AP genotypes on fibrinogen expression could be of importance for future approaches on diagnostic algorithms based on fibrinogen levels.Thus, knowledge on the influence of fibrinogen, F13A and A2AP, which are known to influence the process of fibrin crosslinking as well as antifibrinolytic capacity of fibrin clots, influence genetic regulation of fibrinogen synthesis by genetic variability of the fibrinogen gene loci FGB, FGA and FGG. It could be assumed that this phenomenon is related to their influence on inflammation control. As our findings have been derived from a cohort of pregnant women, confirmatory studies in other patient groups under proinflammatory stimulation are needed.Genetic polymorphisms of