FMR1 premutation (PM: 55–199 CGG)/full mutation (FM: >200 CGG) alleles or the presence of unmethylated FM (UFM) have been associated with a less severe fragile X syndrome (FXS) phenotype and fragile X associated tremor/ataxia syndrome (FXTAS)—a late onset neurodegenerative disorder. We describe a 38 year old male carrying a 100% methylated FM detected with Southern blot (SB), which is consistent with complete silencing of FMR1 and a diagnosis of fragile X syndrome. However, his formal cognitive scores were not at the most severe end of the FXS phenotype and he displayed tremor and ataxic gait. With the association of UFM with FXTAS, we speculated that his ataxia might be related to an undetected proportion of UFM alleles. Such UFM alleles were confirmed by more sensitive PCR based methylation testing showing FM methylation between 60% and 70% in blood, buccal, and saliva samples and real-time PCR analysis showing incomplete silencing of FMR1. While he did not meet diagnostic criteria for FXTAS based on MRI findings, the underlying cause of his ataxia may be related to UFM alleles not detected by SB, and follow-up clinical and molecular assessment are justified if his symptoms worsen.Mosaicism for  FMR1 are termed full mutations (FM) and are associated with epigenetic silencing of the FMR1 gene [FMR1 transcription usually results from abnormal methylation of the FMR1 promoter [FMR1 protein (FMRP). Absence of FMRP, which is a protein essential for normal neurodevelopment, is the primary cause of the fragile X syndrome (FXS) [CGG expansions of more than 200 CGG repeats within the 5′untranslated end of me (FXS) . FXS is me (FXS)  with a pFMR1 promoter similar to normal size alleles with less than 44 repeats [FMR1 mRNA levels and paradoxically impaired translation and decreased FMRP levels [FMR1 transcription usually leads to gain-of-function toxicity resulting in aggregation of proteins by the excessive mRNA, formation of ubiquitin-positive inclusion bodies in the brain and other tissues, mitochondrial dysfunction, and excessive cell death [ASFMR1/FMR4 [FMR5, and FMR6 [The more common CGG triplet expansions of 55 to 199 CGG repeats are termed premutations (PM) and are found in approximately 1 in 450 males and 1 in 150 females in the general population . In cont repeats , but areP levels . Increasll death ,11. Thisll death . Other mll death , over-exand FMR6 , and repand FMR6 .FMR1 mRNA were reported in blood from all three cases, CGG size testing in other peripheral tissues identified PM/FM mosaicism for one of these [Although FXS and FXTAS are regarded as distinct disorders, several lines of evidence now suggest that they can be comorbid . Specifiof these . More reof these .FMR1 promoter in blood, detected using Southern blot analysis of the NruI restriction site within the FMR1 CpG island. This approach is the gold standard FXS diagnostic test where full methylation is understood to indicate complete silencing of FMR1 [FMR1 promoter and FMR1 expression that was reduced, but not silenced. While this individual did not meet the diagnostic criteria for FXTAS, he did show early onset ataxia in his 30s.In this study, we describe a 38 year old FXS male with a fully methylated  of FMR1 . HoweverThe follow-up clinical and molecular assessments consequent to assessment of his tremor and ataxia symptoms in the neurology clinic were conducted as part of the FREE FX study, approved by The Royal Children’s Hospital Research and Ethics Committee.® DNA Self-Collection Kit , and buccal samples collected using the Master Amp Buccal Swab Brush kit . DNA was isolated from these sample types using the NucleoSpin® Tissue genomic DNA extraction kit . Five mL of blood was used for peripheral blood mononuclear cell (PBMC) isolation using Ficoll gradient separation [CGG triplet repeat sizing and methylation testing were performed on 15 mL of peripheral blood collected in EDTA tubes, saliva samples collected using the Orageneparation . RNA wasNruI restriction site located within the CpG island 5′ of the CGG expansion, which is the “gold standard” recommended in FXS diagnostics [NruI/HindIII. The DNA probe Pfxa3a was radio-labelled with P32  and used to detect FMR1 allele-specific restriction fragments by autoradiography as previously described [FMR1 PCR Kit  was used to confirm CGG triplet repeat sizing and to perform methylation analysis of two HpaII sites: 5′ and 3′ of the CGG expansion using blood DNA.Initial CGG repeat sizing in all samples was performed using polymerase chain reaction (PCR) as previously described . Methylagnostics . Methylagnostics . Five μgescribed . The AmpThe Sequenom MALDI-TOF MS EpiTYPER system  and Methylation Specific Quantitative Melt Analysis (MS-QMA) were used to analyse mean methylation of the fragile X related epigenetic element 2  in blood, buccal, and saliva samples as previously described . SpecifiFMR1 mRNA analysis was performed using the relative standard curve real-time PCR method, where the mean of FMR1-5′ and FMR1-3′ assay outputs was normalized to average expression of three internal control genes , as previously described [FMR1 mRNA expression for each sample.escribed . For eacPCR and fragment analyses were used to examine repeat regions associated Friedreich’s ataxia (FA) and spinocerebellar ataxias (SCA) as part of the molecular diagnostics follow-up, using standard diagnostic protocols as previously described ,25.A 38 year old intellectually disabled male with a previous diagnosis of fragile X syndrome presented to a neurology clinic with a history of intermittent tremor and increasing unsteadiness over the previous several months. His medical history included type 2 diabetes mellitus and hyperthyroidism due to Grave’s disease. His medications included metformin, gliclazide, insulin, telmisartan, and rabeprazole. His living arrangements were semi-supervised in a flat downstairs from his parents. He has no family history of other movement disorders, including essential tremor; he has only consumed small amounts of alcohol in social settings and there was no history of substance abuse.His physical examination demonstrated a high frequency of up-down action tremor without any resting tremor, truncal tremor, titubation, or extrapyramidal signs. Although he had no cerebellar signs in his limbs or nystagmus, he demonstrated a slightly wide-based gait and was unable to complete tandem gait suggesting a mild degree of cerebellar dysfunction. No other involuntary movements or pyramidal signs or apraxia were present. His brain magnetic resonance imaging revealed mild cerebellar atrophy .Formal assessments of cognitive and behavioural impairments previously associated with the FXS phenotype were performed at 38 years of age, six months after the initial visit. While he was cognitively impaired with full scale IQ (FSIQ) of 50 , the scoBlood biochemistry investigations, including thyroid function tests, vitamin B12, folate, autoimmune, and paraneoplastic antibody panel, were all within normal limits. Despite a history of suboptimally controlled diabetes, there was no evidence of sensory or motor neuropathy on the nerve conduction studies, ruling out other possible causes of tremor and ataxia. While PCR based testing for other causes of ataxia did not support Friedrich’s ataxia or spinocerebellar ataxias type 1, 2, 3, 6, and 7, it is possible that the FXS patient has another neurological disorder that would explain the early onset ataxia.NruI site within the FMR1 CpG island (FMR1 promoter (60%–70%). Presence of partially methylated FM alleles was further confirmed by (i) AmplideX TP-mPCR through analysis of HpaII site methylation on either side of the CGG repeat (72% methylation)  RNA toxicity at least in a minority of cells and (ii) observed symptoms of ataxia. This is consistent with another 33 year old male case where tissue mosaicism for FM methylation, similarly, did not show FMR1 mRNA levels above the normal range, however, he had clinical and MRI findings consistent with FXTAS [The original diagnostic investigation for FXS at 14 years of age, based on morphological features and cytogenetic testing of cells expressing the Xq27.3 fragile site, was negative. At 38 years of age, he was again referred for FXS testing after his nephew was diagnosed with this syndrome. The follow-up testing using Southern blot revealed a FM expansion but did not use methylation-sensitive enzyme/s. Methylation sensitive Southern blot analysis performed that same year identified a FM allele of 480 CGG repeats that had a 100% methylated G island B. This, ylation) F and  reduced but not silenced FMR1 transcription; (ii) blood biochemistry results ruling out other causes of ataxia; (iii) his cognitive impairment being not as severe as previously reported in most fully methylated FM males. All of this suggested that in this FXS male, FM alleles in a proportion of cells had unmethylated FM alleles and thus were able to express potentially toxic FMR1 mRNA. This was supported by FREE2 methylation testing in blood, buccal, and saliva, AmplideX methylation testing, and FMR1 mRNA analysis in blood. Two potential explanations for the discordance in the methylation results obtained between Southern blot and the other techniques are: (i) the analytical sensitivity of Southern blot methylation analysis is 20% [NruI restriction site methylation is different to methylation of the HpaII restriction sites targeted by AmplideX and the FREE2 region targeted by MALDI-TOF MS and MS-QMA. Together this evidence supports the conclusion that FMR1 mRNA is expressed from expanded FM alleles that may be toxic, even in individuals who appear to have a fully methylated FM by the “gold standard” methylation-sensitive Southern blot test. Furthermore, co-morbidity of FXS and ataxia may be more common than previously realised as ataxia has been noted in some older FXS FM patients identified using methylation-sensitive Southern blot in previously described cohorts [FMR1 promoter  and in multiple tissues, along with testing for FMR1 expression analysis if RNA is available. This additional diagnostic information may better explain the clinical phenotype and provide some assurance to the patients and their family that this is another manifestation of the FMR1 PM or unmethylated FM alleles, rather than a new, unexplained aetiology. Whether the underlying cause of this patient’s ataxia is the same as for FXTAS is unknown, but follow-up study is justified to consider if his symptoms worsen.This FXS patient demonstrated early onset ataxia without MRI changes beyond mild cerebellar atrophy. While his Southern blot results showed a FM with complete methylation of the s is 20% , meaning cohorts . We, the


Despite recent advances in screening methods, lung cancer remains the leading cause of cancer-related deaths worldwide. By the time lung cancer becomes symptomatic and patients seek treatment, it is often too advanced for curative measures. Low-dose computed tomography (CT) screening has been shown to reduce mortality in patients at high risk of lung cancer. We present a 66-year-old man with a 50-pack-year smoking history who had a right upper lobe (RUL) pulmonary nodule and left lower lobe (LLL) consolidation on a screening CT. He reported a weight loss of 45 pounds over 3 months, had recently been hospitalized for hyponatremia, and was notably cachectic. A CT of the chest showed a stable LLL mass-like consolidation and a 9 × 21 mm subsolid lesion in the RUL. Navigational bronchoscopy biopsy of the RUL lesion revealed squamous non–small cell lung cancer (NSCLC). Endobronchial ultrasound-guided transbronchial needle aspiration of the LLL lesion revealed small cell lung cancer (SCLC). The final diagnosis was a right-sided Stage I NSCLC (squamous) and a left-sided limited SCLC. The RUL NSCLC was treated with stereotactic radiation; the LLL SCLC was treated with concurrent chemotherapy and radiation. In patients with multiple lung nodules, a diagnosis of synchronous multiple primary lung cancers (MPLCs) is crucial, as inadvertent upstaging of patients with MPLC (to T3 and/or T4 tumors) can lead to erroneous staging, inaccurate prognosis, and improper treatment. Recent advances in the diagnosis of small pulmonary nodules via navigational bronchoscopy and management of these lesions dramatically affect a patient's overall prognosis. Lung cancer is by far the leading cause of cancer deaths in both men and women, with roughly 222,500 new cases of lung cancer expected to be diagnosed in 2017 alone  or the LThe most common incidental finding is a single primary malignancy, but synchronous multiple primary lung cancers in varied stages are occasionally diagnosed based on lung cancer screening results . However1 of 2.58 L (81% predicted). The LLL consolidation was evident on a chest radiograph 6 months before his current presentation, and the lesion had been biopsied by his local pulmonologist via conventional bronchoscopy with no evidence of malignancy.A 66-year-old man with a 50-pack-year smoking history and severe chronic obstructive pulmonary disease (COPD) presented to our clinic with a new right upper lobe (RUL) pulmonary nodule and a chronic left lower lobe (LLL) consolidation on screening computed tomography (CT). His pulmonary function tests (PFTs) showed airflow obstruction with an FEVThe patient reported a 45-pound weight loss over the course of three months, as well as a recent hospitalization for severe hyponatremia (109 mEq/L). Upon physical examination, the patient was noted to be cachectic, with bilateral decreased air entry. CT of the chest showed a stable LLL consolidation along with a 9 × 21 mm subsolid lesion in the RUL. Navigational bronchoscopy and biopsy of the RUL lesion revealed squamous NSCLC with positive CK5, p63, and TTF-1 markers Figures . The LLLImmunohistochemical markers were consistent with an undifferentiated SCLC that was positive for CAM 5.2, TTF-1, CD56, and synaptophysin and negative for p63 and CK5 . The finLung cancer screening has been shown to decrease mortality associated with lung cancer by detecting early-stage lung cancer in high-risk patients . PatientRecent advances in the diagnosis of small pulmonary nodules via navigational bronchoscopy and the management of these nodules  can significantly affect patients' prognosis, survival, and treatment. To diagnose synchronous MPLCs, physicians must adhere to strict criteria and obtain tissue samples of both lesions. These samples must each be malignant and must arise independently in the lung. Benign nodules, infectious processes, or metastases from extrapulmonary sources must be excluded. Further complicating the diagnostic process is the fact that up to 50% of synchronous MPLCs are composed of multiple adenocarcinomas .different histology from a separate focus,same histology but anatomically distinct lesions without involvement of the mediastinum (N2/N3) and without systemic metastases,same histology but clearly different lesions  .The accepted criteria for distinguishing a second primary malignancy from metastasis are Our patient met the criteria of different histology, anatomically distinct lesions, and different biomarkers. Before biopsy, the absence of mediastinal involvement on his PET scan triggered suspicion for synchronous MPLCs. Any patient with multiple lung nodules without mediastinal involvement should undergo tissue sampling of all lung lesions for definitive diagnosis.Current recommendations suggest that clinicians initiate a discussion about lung cancer screening with patients who meet certain criteria. Patients aged 55 to 74 years who have at least a 30-pack-year smoking history, who currently smoke, or who have quit within the past 15 years and those who are in relatively good health qualify for screening . The recOur case depicts the insidious development of synchronous primary lung cancer with both NSCLC and SCLC, and with this case come several crucial teaching points. Patients diagnosed with one cancer are at increased risk of a second malignancy, and patients with one pulmonary neoplasm are at increased risk of a second lung tumor . MPLCs a


KRAS status validated by digital droplet PCR. A higher median level of total cfDNA was observed in patients with PDAC (585 ng/ml) compared to either patients with CP (300 ng/ml) or healthy controls (175 ng/ml). PDAC tissue showed wide mutational heterogeneity, whereas KRAS was the most commonly mutated gene in cfDNA of patients with PDAC and was significantly associated with a poor disease specific survival (p=0.018). This study demonstrates that tNGS of cfDNA is feasible to characterise the circulating genomic profile in PDAC and that driver mutations in KRAS have prognostic value but cannot currently be used to detect early emergence of disease. Importantly, monitoring total cfDNA levels may have utility in individuals “at risk” and warrants further investigation.The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed late so that surgery is rarely curative. Earlier detection could significantly increase the likelihood of successful treatment and improve survival. The aim of the study was to provide proof of principle that point mutations in key cancer genes can be identified by sequencing circulating free DNA (cfDNA) and that this could be used to detect early PDACs and potentially, premalignant lesions, to help target early effective treatment. Targeted next generation sequencing (tNGS) analysis of mutation hotspots in 50 cancer genes was conducted in 26 patients with PDAC, 14 patients with chronic pancreatitis (CP) and 12 healthy controls with  Pancreatic cancer is the eleventh most common cancer in the UK, accounting for 3% of all newly diagnosed cancers, but is the fifth leading cause of cancer-related death . The incKRAS at a relatively early stage, inactivation of the tumour suppressor gene CDKN2A at an intermediate stage and at a late stage, inactivation of the tumour suppressor genes TP53 and SMAD4 KRAS mutaiewed in  and founin vitro  but thisp.G12R c.G>C and pKRAS gene. These results demonstrate that point mutations in key cancer genes can be identified by tNGS of cfDNA. Moreover, monitoring the levels of cfDNA in PDAC patients for driver mutations in the KRAS gene has prognostic value warranting a larger study. Unfortunately, this study was not able to help detect early PDACs or premalignant lesions of pancreatic cancer but since this study, there have been more advances in tNGS, allowing for better detection of low frequency variants, and combined with the recommendations for standardization of study cohorts and extraction methods, this may help with future validation of cfDNA biomarkers.In conclusion, we demonstrated mutational heterogeneity in primary tumour tissue of patients with PDAC, and found circulating tumour derived DNA in 27% of patients based on detection of mutations in the A total of 59 patients were analysed for the study; 51 had amplifiable cfDNA from plasma and 18 had amplifiable DNA from formalin fixed paraffin embedded (FFPE) tissue samples. Full details including clinicopathological characteristics are presented in Pancreatic cancer cell lines  obtained from ATCC  were used for assay development and validation. Cells were cultured in DMEM + 10% FBS . Prior to extraction cells were trypsinised and washed in 1X PBS (Sigma). Cells were pelleted and stored at −80°C. Cell pellets were reconstituted in 200μl of 1X PBS before extraction.cfDNA was extracted from plasma using the QIAamp Circulating Nucleic Acid kit  as per the manufacturer's instructions. DNA was extracted from pancreatic cancer cell lines using the DNA blood mini kit (Qiagen) according to the manufacturer's instructions. FFPE tissue blocks with matching H&E were retrieved from the histopathology archive and reviewed by a consultant Histopathologist. DNA from FFPE samples was extracted using the GeneRead DNA FFPE Kit (Qiagen). DNA was quantified using the Qubit 2.0 fluorometer according to manufacturers’ instructions.TM Cancer Hotspot Panel V2  using 10 ng of cfDNA or 20 ng FFPE DNA. Samples were sequenced on the Ion Personal Genome Machine (Ion PGMTM) using Ion 316TM v2 chips according to manufacturer's instructions. Sequencing data was analysed through the Torrent SuiteTM v4.2.0. Reads were aligned against the human genome (hg19) using Alignment v4.0-r77189 and variants called using the coverageAnalysis v4.0-r77897 and variantCaller v4.0-r76860, respectively [http://cancer.sanger.ac.uk/cosmic, last accessed 2nd May 2016). All mutations with a quality score below 20 were omitted and all variants detected in the first or last 10 bases of an amplicon were omitted as likely mispriming events [Reactions were set up using the Ion Ampliseqg events . All varKRAS mutational status of patient samples where possible. 5 ng of cfDNA and 10 ng of FFPE DNA was used in conjunction with Bio-Rad's ddPCRTMKRAS G12/G13 Screening kit according to manufacturers’ instructions  using a Bio-Rad QX200 digital droplet PCR system as previously described [KRAS mutation. Raw fluorescence amplitude was analysed using the Quantasoft version 1.6.6.0320 software to obtain the fractional abundance (FA) of mutant DNA alleles to total (mutant plus wild type) DNA alleles.Droplet digital PCR was used to validate the escribed . For allth September 2015 when any remaining survivors were censored. The Mann Whitney U test was used to examine the levels of cfDNA between PDAC patients with and without distant metastasis and to the Ca19.9 levels. The association between the KRAS status and metastasis was assessed using a Fisher's exact test due to there being less than five cases in some cells. Survival analysis comparing age, gender or KRAS status with disease specific survival for the PDAC patients was conducted using the log rank test and Kaplan-Meier curves. Hazard ratios and 95% confidence intervals where determined using Cox regression analysis as was the relationship between cfDNA levels and disease specific survival. The correlation between KRAS and distant metastasis was confirmed using Spearman rank-order.SPSS version 22 statistical software package was used. A stem and leaf plot was constructed to demonstrate the difference in cfDNA levels between the different groups of patients and the Independent Samples Mann-Whitney U test. For PDAC patients, disease specific survival was calculated from the date of the blood sample until 15PDACPancreatic Ductal AdenocarcinomacfDNACirculating free DNActDNACirculating tumour DNACPChronic PancreatitistNGSTargeted Next Generation SequencingddPCRDroplet Digital PCRPanINPancreatic Intraepithelial Neoplasia


STAT3 and chronic HBV infection has yet to be investigated.Signal transducer and activator of transcription 3 (STAT3) is involved in hepatitis B virus (HBV) infection and HBV-related hepatocellular carcinoma (HCC). The association between polymorphism rs1053005 and haplotypes formed by rs1053004 and rs1053005 in the 3′UTR of STAT3 rs1053004 and rs1053005 polymorphisms were genotyped by TaqMan SNP Genotyping Assays.This study included 567 patients with chronic HBV infection , 98 HBV infection resolvers, and 169 healthy controls. P value by Bonferroni correction (Pc) = 0.002] and allele C (Pc = 0.019) were more frequent in patients with chronic HBV infection than in healthy controls. The rs1053005 genotype GG was also more frequent in patients with chronic HBV infection than in healthy controls (Pc = 0.046). The rs1053004-rs1053005 haplotype T-G was less frequent in patients with chronic HBV infection than in healthy controls (Pc < 0.001). Haplotype C-A was more frequent in patients with liver cirrhosis than in patients with HCC (Pc = 0.042). The rs1053004 genotype TC, rs1053005 genotype AG and rs1053004-rs1053005 haplotype T-A were associated with higher HBV DNA levels.The rs1053004 genotype CC [STAT3 rs1053004 and rs1053005 polymorphisms and haplotypes formed by rs1053004 and rs1053005 are associated with chronic HBV infection and the haplotypes appear to be also associated with the development of liver disease. Studies in large sample sizes of patients and control populations are required to verify and extend these findings.The online version of this article (10.1186/s12881-018-0569-x) contains supplementary material, which is available to authorized users. Hepatitis B virus (HBV) infection, which can result in acute and chronic hepatitis, liver cirrhosis and hepatocellular carcinoma (HCC), remains a worldwide public health issue , 2.The intensity of immuno-inflammatory cells and cytokines is involved in the disease course and the development of various clinical consequences of HBV infection –5. SignaSTAT3 may have predisposing effects on the susceptibility to HBV infection and HBV-related liver diseases. Polymorphisms in the 3′ untranslated region (UTR) may be functionally relevant because this region usually contains regulatory elements that may post-transcriptionally regulate gene expression. There are 4 common single nucleotide polymorphisms (SNPs)  with minor allele frequency (MAF) greater than 0.05 in the 3’ UTR of STAT3  according to manufacturer’s instruction. P value < 0.05 was regarded as statistically significant. Multiple testing correction was performed by the Bonferroni method. The chi-square test or student’s t-test was used to compare parameters between groups. The frequency of genotypes and alleles was determined by direct gene counting method. The chi-square test or Fisher’s exact test was used to estimate the Hardy–Weinberg equilibrium (HWE) and to compare the genotype and allele frequencies between the groups. Odds ratios (OR) with 95% confidence interval (CI) were calculated by logistic regression analyses adjusted for age and sex. Haplotype analysis was performed using SHEsis platform  although its frequency between HBV infection resolvers and patients had no significant difference . Haplotype C-A was more frequent in patients than in healthy controls but the difference was not significant by Bonferroni correction  but these differences were not significant after Bonferroni correction  and HBV DNA levels between patients carrying haplotype C-G and those carrying haplotype C-A were not significantly different  with MAF greater than 0.05 in the 3′UTR of STAT3 . The SNPSTAT3 , 15. TheSTAT3 , this stSTAT3 rs1053004 has been suggested to be involved in chronic HBV infection in Chinese [STAT3 rs1053005 has been shown to be associated with ankylosing spondylitis and autoimmune thyroid disease in Han Chinese population [ Chinese  and Thai Chinese . STAT3 rpulation , 20, to pulation , 22, andpulation . It is iSTAT3 SNPs rs4796793, rs2293152, and rs1053004 were interactively involved in the hepatocarcinogenesis in the host with HBV mutations in Han Chinese [STAT3 SNP rs1053004 was also shown to be contributable to HCC susceptibility in the Thai population [STAT3 3’UTR was shown to act as a promotion factor in HCC development in Chinese population [STAT3 polymorphisms with the susceptibility of chronic HBV infection and the development of liver disease including HCC are complicated.Previous studies showed that  Chinese . The STApulation . In the STAT3 which have been revealed to be associated with human disease. For example, STAT3 rs3816769 and rs744166 polymorphisms were shown to play a significant role in susceptibility to autoimmune thyroid disease Hashimoto’s thyroiditis and Graves’ disease in the Polish population [STAT3 need to be genotyped in chronic HBV infection and HBV-related liver disease including HCC to clarify the detailed profile of STAT3 polymorphisms in HBV infection in future studies.There are other SNPs in pulation . TherefoSTAT3, and did not include replicative patient and control populations to confirm the findings. Therefore, the results appear to be very preliminary. Further studies in large patient and control populations with more polymorphisms genotyped are definitely needed to elucidate the possible role of STAT3 polymorphisms in chronic HBV infection and HBV-related liver diseases.The present study was conducted in small sample sizes of patients and controls, genotyped and analyzed only two polymorphisms in the 3’ UTR of STAT3 rs1053004 and rs1053005 polymorphisms and haplotypes formed by rs1053004 and rs1053005 are associated with chronic HBV infection and the haplotypes appear to be also associated with the development of liver disease. Studies in large sample sizes of patient and control populations are required to confirm and extend these findings. Studies are also needed to elucidate the underlying mechanisms related to the potential association between STAT3 polymorphisms and chronic HBV infection and HBV-related liver diseases.This study indicates that Additional file 1:Table S1. Associations of STAT3 rs1053004 and rs1053005 polymorphisms and rs1053004-rs1053005 haplotypes with HBV DNA levels. (DOC 101 kb)


Systemic sclerosis  is an uncommon autoimmune rheumatic disease characterised by autoimmunity, vasculopathy and fibrosis. Gene expression profiling distinguishes scleroderma from normal skin, and can detect different subsets of disease, with potential to identify prognostic biomarkers of organ involvement or response to therapy. We have performed gene expression profiling in skin samples from patients with limited cutaneous SSc (lcSSc).Total RNA was extracted from clinically uninvolved skin biopsies of 15 patients with lcSSc and 8 healthy controls (HC). Gene expression profiling was performed on a DNA oligonucleotide microarray chip. Differentially expressed genes (DEG) were identified using significance analysis of microarrays (SAM). Functional enrichment analysis of gene signatures was done via g:Profiler.There were 218 DEG between lcSSc and HC samples : 181/218 DEG were upregulated in lcSSc samples. Hierarchical clustering of DEG suggested the presence of two separate groups of lcSSc samples: “limited 1” and “limited 2”. The limited-1 group  showed upregulation of genes involved in cell adhesion, cardiovascular system (CVS) development, extracellular matrix and immune and inflammatory response. The CVS development signature was of particular interest as its genes showed very strong enrichment in response to wounding, response to transforming growth factor (TGF)-β and kinase cascade. Neither limited-2 samples  nor HC samples showed functional enrichment. There were no significant differences in demographic or clinical parameters between these two groups. These results were confirmed using a second independent cohort.Our study suggests the presence of molecular subsets in lcSSc based on gene expression profiling of biopsies from uninvolved skin. This may reflect important differences in pathogenesis within these patient groups. We identify differential expression of a subset of genes that relate to CVS and are enriched in fibrotic signalling. This may shed light on mechanisms of vascular disease in SSc. The enrichment in profibrotic profile suggests that dysregulated gene expression may contribute to vasculopathy and fibrosis in different disease subsets.The online version of this article (doi:10.1186/s13075-017-1360-7) contains supplementary material, which is available to authorized users. Systemic sclerosis  represents a major clinical challenge and offers insight into fundamental processes relating to autoimmunity, fibrosis and vascular injury and pathology. It is an uncommon immune-mediated rheumatic disease with a very high clinical burden, high mortality and limited treatment options , 2 and pThe limited cutaneous subset of SSc (lcSSc) is characterised by less severe and extensive skin fibrosis but patients can develop major internal organ complications and the vascular manifestations of SSc, particularly pulmonary arterial hypertension and digital ulceration, are prominent in this subset . DetaileIn this study, we demonstrate differential gene expression in a cohort of lcSSc patients and healthy controls and describe a distinct lcSSc subgroup not identifiable by clinical or serological assessment showing enrichment in cell adhesion, cardiovascular system (CVS) development and extracellular matrix genes. We confirm our findings in a second independent cohort of samples. The CVS development signature was significantly different between both subgroups of limited patients and a control group.Demographic information, clinical history including organ involvement, other diagnoses and extent of skin involvement, autoantibody profiles and treatments were retrieved from medical notes or obtained at the time of skin biopsy. Diagnosis of SSc was made according to the 2013 American College of Rheumatologists (ACR)/European League Against Rheumatism (EULAR) classification criteria and assignment to the limited cutaneous subset reflected the distribution and extent of skin thickening at the time of biopsy together with other typical disease characteristics . AutoantTM RNA stabilisation reagent  at 4 °C overnight followed by longer-term storage at -70 °C. To avoid a potential confounding effect of different degrees of skin thickening or fibrosis, biopsy sites were selected from skin that was not clinically involved. There were no changes in pigmentation or dryness.Forearm 4-mm skin punch biopsies were performed both in patients with lcSSc and in healthy controls, and were stored for extraction in RNAlaterTissue homogenization was performed using Qiagen TissueLyser II. RNA purification was carried out in a QIAcube with Qiagen RNeasy Fibrous Tissue Mini Kit . The Agilent 2100 Bioanalyzer  was used to assess the RNA integrity of samples with numbers >7. RNA concentration was measured with Thermo Scientific NanoDrop 2000 Spectrophotometer . A measure of 200 ng of total RNA was amplified and labelled with Agilent's Quick-Amp Labelling Kit. Cy3-labelled samples and Cy5-labelled Universal Human Reference RNA  were co-hybridized to Agilent's Human Genome (4 × 44 K) Microarrays (G4112F). Data were log2 lowess-normalised and filtered for probes with intensity ≥1.5-fold over local background in Cy3 or Cy5 channels. Data were multiplied by -1 to convert them to log2(Cy3/Cy5) ratios. Probes with >20% missing data were excluded.Expression data were pre-processed using GenePattern  modules Differentially expressed genes were identified using significance analysis of microarrays (SAM) . Two-claThere were 23 subjects included in the discovery cohort: 15 patients with lcSSc and 8 healthy controls. The study samples were collected and analysed in two stages, first in 10 biopsies from patients with lcSSc and from 5 healthy controls that generated the initial CVS signature, and then in samples from an extended cohort with an additional 6 patients with lcSSc and 3 healthy controls. These later samples were collected independently of the first set of samples.Demographics, clinical characteristics, organ-based disease and therapies are listed in Table ANGPT2, CD163, COMP, CTGF and TIMP2, among others  between lcSSc and healthy control samples  <10%). Of these 218 genes, 181 (83%) were upregulated in lcSSc samples and were significantly enriched in several terms related to the extracellular matrix (ECM), e.g. ECM organisation and ECM component and response to growth factor, tissue development and regulation of the serine/threonine kinase signalling pathway. This gene signature included genes previously implicated in the pathogenesis of SSc such as ers Fig. . The fulEven though we specifically asked for genes differentially expressed between lcSSc samples and healthy controls, 6 lcSSc samples (5 unique patients) clustered with controls, whereas the remaining 13 lcSSc samples (10 unique patients) formed a distinct cluster Fig. . We desiSince comparison between lcSSc and controls was suggestive of the presence of two lcSSc groups, we performed multiclass SAM to identify DEG between limited-1, limited-2 and healthy control samples: 807 genes were differentially expressed between these three groups (FDR <10%). Again, limited-2 samples clustered with controls and separately from the limited-1 group  and strong enrichment in cell adhesion, response to growth factor, mitogen-activated protein kinase (MAPK) cascade and response to wounding (p < 10-5), among others. Enrichment in immune signalling was comparatively weak (e.g. p = 0.0183 for immune system process and p = 0.0208 for inflammatory response). The entire g:Profiler output is listed in Additional file Genes with significantly increased expression in either the limited-2 group or in healthy controls were not functionally enriched. Genes with significantly increased expression in samples from the limited-1 group  displayed very strong enrichment in functional terms related to ECM and vasculature development (p = 3.01 × 10-14): 70 out of 475 genes with increased expression in limited-1 samples were involved in this biological process. This set of 70 genes essentially recaptured many of the biological themes observed in the bigger limited-1 gene expression signature. For example, there was very strong enrichment in angiogenesis, response to growth factor and cell proliferation (p < 10-10) and strong enrichment in ECM, cartilage development, MAPK cascade, cell adhesion and response to wounding (p < 10-5), among others. It was also strongly enriched in response to transforming growth factor (TGF)-β . Additional file For the limited-1 group, the term with the most significant functional enrichment was cardiovascular system development , with samples comprising 24 lcSSc and 4 control samples. Similar to this study cohort, analysis of differential expression between lcSSc and control samples suggested the presence of two subgroups of patients with lcSSc (group 1 with 14 lcSSc samples and group 2 with 10 lcSSc samples). We then compared the gene expression of the CVS development gene signature across subgroups of lcSSc patients and controls from the validation study. This gene expression signature was significantly different among both subgroups of patients with LcSSc and a control group Fig. , paralleIn this study we have assessed molecular heterogeneity in gene expression profiles from skin biopsies taken from uninvolved skin of lcSSc patients compared with matched healthy controls. We have identified two subgroups within the lcSSc patient population in this study, which we termed limited 1 and limited 2. Patients from the limited-2 subgroup correspond to a third of the lcSSc cases and are generally characterised by a subtle alteration in gene expression that resembles but is distinct from the control samples. The majority of lcSSc cases cluster into a limited-1 subgroup associated with a substantial number of genes with significant differential expression, which are involved in multiple functional terms with known or potential relevance to SSc pathogenesis. We have confirmed our findings in a second cohort.COMP, THBS1 and CTGF. These have traditionally been considered as pro-fibrotic markers, but all have a role in the regulation of vascular function [MMP19 and COL4A1 were also included. It is also attractive to consider that recapitulation of developmental gene expression programmes may be central to susceptibility to development of SSc since it can be envisaged as a disease of perturbed connective tissue repair. There is a strong precedent for the same genetic pathways and programmes that are used in embryonic and post-natal growth and development to be recapitulated in acquired disease [Most compelling is the identification of a cardiovascular system (CVS) development gene expression signature. This is interesting because of the well-recognised vascular abnormalities that are seen in lcSSc . The idefunction –25. More disease . This ma disease .It is also notable that there were no clear clinical or serological associations with the molecular subgroups of lcSSc. This is relevant since it suggests that gene-expression-based subsets may indeed add to the clinical and serological factors that are already used in the clinic to subgroup patients. This would be analogous to the intrinsic subsets of diffuse cutaneous SSc (dcSSc) that have been reported and that are already of clinical utility . Of noteIt is striking that many of the genes involved in CVS development are also seen in other relevant pathways such as ECM and response to TGF-β. Not only does this give some key candidate genes and pathways that could be perturbed in SSc but it also is a reminder that these factors that have been focussed on for a role in fibrosis may also have other roles in the biology or the disease. Thus it is plausible that the patterns of gene expression are altered in SSc and that this may have distinct consequences depending upon the stage and subset of disease. Further work will be required to assess whether these differences in expression reflect susceptibility to SSc that depends on genetic or epigenetic factors or whether they are reflective of pathogenetic processes that are occurring within the clinically uninvolved skin in limited SSc.Strengths of the study include the well-characterised patients from a single centre, which may reduce the variability that can be a hallmark of multicentre cohorts and ensures standard classification and clinical evaluation. In addition, the use of well-established gene expression analysis platforms and semi-automated sample processing minimises technical variation that has been a limitation in some studies. Inclusion of a matched control group of healthy individuals was important to allow reliable interpretation of the “limited” gene expression signature.Weaknesses of the study are the limitations of a relatively small study cohort that may not allow generalisability of our findings. However, the results are in line with those previously reported for subjects with lcSSc included in earlier gene expression studies . We haveWe have not included patients with clinically involved forearm skin in this study. There are no adequately powered studies that confirm concordance between clinically involved and uninvolved skin but previous data do suggest this; these confirmatory studies are required to extend and validate our findings further as part of a larger future study of gene expression in lcSSc. Involved distal skin is not biopsied in our patients due to concerns about wound healing. Finally, both further post-transcriptomic functional studies, and modern techniques that allow structural analysis of mRNA expression most notably to examine the dermal microcirculation and perivascular space would localise gene expression changes and verify that differential gene expression, particularly from the CVS development cluster, are reflected by differential protein expression.We showed that gene expression profiling of biopsies from uninvolved skin in lcSSc differentiates two potential subgroups that overlap with other clinical and serological features. This may reflect important differences in pathogenesis within these patient groups. In addition, we identified differential expression of a subset of genes that relate to CVS development. Since the lcSSc subset is characterised by vasculopathy in the skin and internal organs, this may shed light on underlying mechanisms of vascular disease in SSc. The clinical implications of our findings will need to be analysed in future larger studies.Additional file 1:Genes significantly differentially expressed between lcSSc and control groups. Green cells: genes with increased expression in controls. Yellow cells: genes with increased expression in lcSSc samples. (XLSX 16 kb)Additional file 2:Genes significantly differentially expressed between the limited-1, limited-2 and control groups. Orange cells: genes with increased expression in limited 1 group. Green cells: genes with increased expression in controls. Grey cells: genes with increased expression in limited 2 group. (XLSX 38 kb)Additional file 3:p value: significance of enrichment in a given term corrected for multiple hypothesis testing using default g:GOSt method g:SCS. Q&T: overlap between genes in the query (Q) and genes in the genome annotated to a given term (T). t type: term category - Gene Ontology: Biological Process (BP), Molecular Function (MF), Cellular Component (CC); KEGG (keg); Reactome (rea). t name: term name. Q&T list: list of genes forming the overlap between query (Q) and genome lists for a given term (T). (XLSX 25 kb)g:Profiler output for 475 genes with increased expression in the limited-1 group . Additional files Additional file 4:p value: significance of enrichment in a given term corrected for multiple hypothesis testing using default g:GOSt method g:SCS. Q&T: overlap between genes in the query (Q) and genes in the genome annotated to a given term (T). t type: term category - Gene Ontology: Biological Process (BP), Molecular Function (MF), Cellular Component (CC); KEGG (keg); Reactome (rea). t name: term name. Q&T list: list of genes forming the overlap between query (Q) and genome lists for a given term (T). (XLSX 29 kb)g:Profiler output for 70 genes with increased expression in the limited-1 group annotated to cardiovascular system development. Additional file 4 contains the following column headers. Descriptions are as follows:


Siphoviridae, as prevalent in the soil samples and other compared viromes. Functional analysis and other metaviromes showed a relatively high frequency of phage-related and structural proteins. Phylogenetic analysis of PolB, PolB2, terL and T7gp17 genes indicated that many viral sequences are closely related to the order Caudovirales, while the remainder were distinct from known isolates. The use of single virome which only includes double stranded DNA viruses limits this study. Novel phage sequences were detected, presenting an opportunity for future studies aimed at targeting novel genetic resources for applied biotechnology.The Kogelberg Biosphere Reserve in the Cape Floral Kingdom in South Africa is known for its unique plant biodiversity. The potential presence of unique microbial and viral biodiversity associated with this unique plant biodiversity led us to explore the fynbos soil using metaviromic techniques. In this study, metaviromes of a soil community from the Kogelberg Biosphere Reserve has been characterised in detail for the first time. Metaviromic DNA was recovered from soil and sequenced by Next Generation Sequencing. The MetaVir, MG-RAST and VIROME bioinformatics pipelines were used to analyse taxonomic composition, phylogenetic and functional assessments of the sequences. Taxonomic composition revealed members of the order Caudovirales, in particular the family  Fynbos (fine bush) is the main vegetation type of this region with the Proteaceae, Ericaceae and Restionaceae families dominating Kogelberg Biosphere Reserve Fynbos vegetation. Within this region, the fynbos comprises approximately 9000 plant species of which 70% are endemic to the region3. Fynbos vegetation types survive on highly heterogeneous, acidic, sandy, well-leached and infertile soils. The fynbos plants also survive invasions by foreign plants4 and seasonal drought conditions5.The Cape Floristic Region situated in the Western Cape province of South Africa is one of five Mediterranean-type ecosystems in the world6 and form complex symbiotic relationships with plants7. Plant-associated microorganism studies have shown high microbial diversity in fynbos soils2, where they play a role in sustaining plant communities8. A study focusing on the linkage between fynbos soil microbial diversity and plant diversity showed the presence of novel taxa and of bacteria specifically associated with the rhizospheric zone9. Studies on ammonium-oxidizing bacteria demonstrated that plant-species specific and monophyletic ammonium oxidizing bacterial clades were present in fynbos soils10, where abundance might be driven by the acidic and oligotrophic nature of these soils11. There is evidence that above-ground floral communities are implicated in shaping microbial communities13, and that some microbial clades show a high level of plant–host specificity10. This is consistent with the general concept of the mutualistic relationships between the plants and the microbial communities in fynbos soils14.Microorganisms make up a great proportion of the living population in the biosphere. They provide important ecosystem services in edaphic habitats15. Virus diversity associated with fynbos plants from Kogelberg Biosphere Reserve fynbos soil has never been thoroughly investigated16. The difficulty of culturing viruses, which are absolutely dependent on a cell host to provide the apparatus for replication and production of progeny virions, presents a barrier to fully accessing viral biodiversity. This is a particular issue in poorly studied habitats, such as fynbos soil, where the true microbial (host) diversity is largely unknown and most microbial phylotypes have never been cultured17. The biodiversity and ecology of viruses in many soils therefore remain poorly investigated and poorly understood18.Soil-borne viruses, including phages, are of great importance in edaphic habitats due to their ability to transfer genes from host to host and as a potential cause of microbial mortality (leading to changes in turnover and concentration of nutrients and gases), processes that can profoundly influence the ecology of soil biological communities18, rice paddy soil20, Antarctic cold desert soil22 and hot desert hypolithic niche communities23 have been reported in recent years and have significantly advanced the field of soil viral ecology24. These studies have also facilitated the discovery of novel virus genomes23 and novel viral enzymes25.Metaviromic surveys of terrestrial environments such as hot desert soil28. Studies on taxonomic composition using public metaviromic databases for viral diversity estimations have shown that a majority of environmental virus sequences are unknown19: ~70% of sequences have no homologs in public databases and are therefore typically labelled “viral dark matter”30. Bacteriophages constitute the largest known group of viruses found in both aquatic31 and soil environments33.However, surveys of viral diversity using NGS sequencing techniques in conjunction with metaviromic databases have focused principally on aquatic environmentsHere we report the first investigation of virus diversity in a unique soil type (fynbos soil) using metaviromic approaches. The metavirome of Kogelberg Biosphere Reserve fynbos soil was characterised in terms of diversity and functional composition and adds a new level of understanding to the exceptional biodiversity of this habitat.34. The isolated virus particles from the fynbos soil were tailed, spherical or filamentous . TEM analysis of the virus preparations showed that the majority of the isolated virus particles were morphologically similar to known virus taxonomic groups35. The undetermined spherical or filamentous morphologies in TEM micrographs could be bona fide but uncharacterised viral structures. Spherical particles resembling capsid structures could be members of the Leviviridae, Partitiviridae, Chrysoviridae, Totiviridae or Tectiviridae families, or small plant viruses34. Filamentous particles may possibly correspond to the virus structures of the Inovirus genus, the members of which contain circular ssDNA within flexible filamentous virions. The presence of spherical types and filamentous type of virus particles was also reported for Delaware soils32. The aggressive extraction procedure used in the current study may have resulted in a high incidence of phage tail breakage and the generation of tailless phages36.These results are in a good agreement with previously published findings showing the high dominance of tailed phages in soils from various geographic areas37 and VIROME38, were used for analysis of the contigs, while MG-RAST39 was used for the analysis of the uploaded reads . MG-RAST core analysis and annotation depends heavily on the SEED database which is largely comprised of bacterial and archaeal genomes41. The majority of the annotated sequences in MG-RAST were mapped to bacterial genomes. This high percentage of bacterial sequences in metaviromes may be due to the presence of unknown prophages in bacterial genomes, phages carrying host genes, relatively large size of bacterial genomes compared to viral genomes and larger size of the microbial genome database which is statistically increasing the chance of matching bacterial sequences. The MG-RAST pipeline was used to analyse the reads, not the contigs and shows, therefore a higher number of predicted features, including more partial CDSs42 No rDNA sequences were found with the MG-RAST and VIROME pipelines, confirming the viral origins of the DNA. The fact that more than 80% of the hits in this study, consistent with previous viral metagenomics studies44, were assigned as hypothetical proteins derived from unknown viruses suggests the presence of a substantial pool of novel viruses.Assembly of the DNA sequence reads yielded 13,595 contigs larger than 500 bp, with an average length of 2,098 bp, accounting for a total of 28,526,478 bp . The results revealed that 37.6% of the contigs represented a significant hit (threshold of 50 on the BLAST bit score). MetaVir identified 18 virus families, in which prokaryotic viruses were the most abundant and dominated by the order Enterobacteria phage phiX174 was also detected in our metavirome sequences. This phage is used for quality control in sample preparation for high-throughput sequencing. Seven sequences from this dataset are similar to the phiX174 genome and were thus disregarded in the taxonomic composition as an artefact of sample processing. Plant viruses were not identified in the dataset, most probably because the majority of plant viruses are RNA viruses which were not sampled in this study.Other viral families and unclassified viruses (dsDNA and ssDNA) were found in low numbers. Putative contamination of 28, soil and hypolithic niche communities23, pond water27 and sea water48  of the metaviromic DNA during library construction. The amplification of metaviromic DNA using phi29 polymerase amplification (Multiple Displacement Amplification) has been reported to be biased towards ssDNA templates19. It is notable, however, that a high abundance of ssDNA viruses has been observed in beach freshwater samples52, where amplification was not used in the preparation of metagenomic DNA. However, in general, other metaviromes which were not amplified using MDA showed a very low number of ssDNA viruses. In general, soils or soil-associated habitats seem to harbour relatively fewer ssDNA viruses and more tailed phages than aquatic ecosystems.The 43, it was found that bacteriophage sequences in Kogelberg Biosphere Reserve fynbos soil made up the majority of the virus fraction. Bacteriophages are common in the environment and are the dominant viral type recovered from metaviromics analyses in soil environments30. This finding was not surprising, given the observations from previous studies53 which showed high prokaryotic abundances in the Kogelberg soil environment. Nevertheless, signature sequences from large dsDNA eukaryotic virus families such as Mimiviridae54 were represented in the Kogelberg Biosphere Reserve library despite the use of small pore size filters in sample preparation. Mimivirus signatures have been reported previously in other soil habitats22. Sequences that were found to be most similar to mimivirus ORFs were also obtained from Sargasso sea water samples, suggesting that these viruses, and their hosts, have a rather cosmopolitan distribution46.Consistent with other data55). Phylogenetic trees were drawn from metavirome sequences on the basis of homology to marker gene reference sequences from the PFAM database. Sequences homologous to the marker genes . This phage is the only sequenced representative of the “Far T4” group of myoviruses  found in a previous diversity analysis of sequences from French lakes28. The Kogelberg polB sequences from this study as well as the gp23 and gp20 marker gene sequences from the French lake study contribute to the expansion of the “Far T4”-like phages dataset.Using the DNA polymerase family B (polB) marker gene, conserved in all dsDNA viruses, Kogelberg Biosphere Reserve sequences appeared to be distantly related to polB2) marker gene, which is conserved in members of Adenoviridae, Salterprovirus, and Ampullaviridae and Podoviridae family viral groups, was analysed. The analysis showed a separate clade of sequences from the Kogelberg Biospheres reserve soil samples. Other polB2 sequences from our dataset were found to be distantly related to members of the Adenoviridae family , the Podoviridae family , the Ampullaviridae family (such as Acidianus-bottle-shaped virus) and the Tectiviridae family .A DNA polymerase family B  was used to visualise the diversity of the Kogelberg Biosphere Reserve fynbos soil Caudovirales  showed similarity to members of both Podoviridae and Siphoviridae families. The translated products of two of these genes (15 and 16) were identified as putative terminase large subunit (gene 15) and terminase small subunit (gene 16) genes, with 88% and 89% amino acid identity to Puniceispirillum phage HMO-2011 and Pseudomonas phage vB_PaeP_Tr60_Ab31, respectively. Both Puniceispirillum phage HMO-2011 and Pseudomonas phage vB_PaeP_Tr60_Ab31 belong to the family Podoviridae. The terL phylogenetic tree . The ERF superfamily proteins are involved in the recombination of phage genomes60. The translated product of gene 41 was identified as a putative gp77 and showed 95% amino acid similarity to a homologue encoded by Mycobacterium phage Che9d . gp77 proteins are known to function as shut-off genes during early stages of phage replication61.The translated product of gene 34 was identified as a putative ERF superfamily protein and showed 55% amino acid identity to a homologue encoded by the unclassified 62.Fifty nine of the translated products of genes in the assembled phage genome showed identity to hypothetical proteins. Of these hypothetical proteins, 56 showed no sequence similarity to known virus families in BLASTp comparison to the RefseqVirus protein database. Three of the genes were predicted to encode glucosaminidase (a hydrolytic enzyme), Phage integrase (a site-specific recombinase that mediates controlled DNA integration and excision) and PDDEXK_1 (nuclease superfamily). Members of this PDDEXK_1 family belong to the PD-(D/E) XK nuclease superfamily. The PD-(D/E)XK nuclease superfamily contains type II restriction endonucleases and many other enzymes involved in DNA recombination and repair63.The protein sequences identified in this analysis indicated the presence of a putative ERF superfamily protein, Phage integrase and PDDEXK_1 family; all proteins implicated in DNA recombination. The ERF superfamily protein encoded by gene 34, whose sequences are expressed during recombination of temperate phages, catalyses annealing of single-stranded DNA chains and pairing of ssDNA with homologous dsDNA, which may function in RecA-dependent and RecA-independent DNA recombination pathwaysA few large contigs contained some predicted ORFs with similarities to phage sequences and coding for specific conserved phage proteins, including terminases, structural proteins  and phage DNA polymerases  clustered together and were clearly distinct from soils which were geographically much closer.Both hypolithic metaviromes  clustered as a single node, despite their widely differing habitat-associated environmental characteristics  and substantial spatial separation (approx. 55 degrees of latitude), suggesting that aridity and not temperature may be the dominant driver of host and viral diversity67. These observations suggest a niche-dependent pattern, where spatially distinct niche environments cluster together and separate from their geographically closer soil counterparts65.The Kogelberg Biosphere Reserve soil metavirome clustered at a single sub-node with the Peruvian rainforest soil metavirome. Both of these habitats experience high annual rainfall and warm temperatures and are characterised by heavily leached and low nutrient status soils, suggesting that soil composition and/or nutrient status may be the strong driver of the host and viral diversity65. Similarly to our study, related habitat types harboured more closely related viral communities, despite the great geographic distances or differing environmental conditions. The common factor in these hyperarid environments is water scarcity, which may be a key driver of community speciation and recruitment in these environments. We conclude that these adaptations and the nature of soil habitat compared to the ‘refuge’ habitat of quartz stones for hypolithic communities, may be the driving force between both communities not to cluster together.Previous study reported that cluster analysis of hypolith and open soil metaviromes from Antarctic and Namib Desert soil has shown that both hypolith metaviromes clustered at a single node and also that both open soil metaviromes displayed an identical patternThe functional implication of the reads was explored using MG-RAST. The Kogelberg Biosphere Reserve metavirome sequences exhibited a high proportion of uncharacterized ORFs, with 2,362,076 sequences showing no significant similarities to proteins in the databases (ORFans). Twelve functional categories were annotated by MG-RAST, each subdivided into distinct subsystems . The “Protein metabolism” and “DNA metabolism” functional categories were also dominant annotations. Many proteins in these functional categories, such as terminases, HNH homing endonucleases, DNA helicases, DNA polymerases and DNA primases, could potentially be of phage origin. These functional groups have also been found to be highly represented in previous metaviromic datasetsAnalysis of the metavirome reads using the KEGG Orthology (KO) database showed metabolism protein families  to be the most commonly identified. Members of the genetic information procession protein family, including replication and repair, transcription and translation proteins, were also commonly identified. Deeper analysis of a subset of annotated contigs identified genes encoding numerous virus structures  and DNA manipulating enzymes .69.From this analysis, we demonstrate that phage-related genes and metabolic genes are highly represented. The virome displayed a strong enrichment in phage-like genes  and lacked typical cellular categories rarely observed in sequenced phages . Cellular categories commonly identified in known phages were retrieved . The highly abundance of virome-associated metabolic genes shows that the phages may have the potential to interfere with the metabolism of their hosts. Our virome analysis, consistent with other virome studies, demonstrate the unexpected picture of global ‘viral’ metabolism, suggesting that viruses might actively dictate the metabolism of infected cells on a global scale28, soil and hypolithic niche communities23, pond water27 and sea water48 mentioned in Fig. The functional assignments from the SEED database of Kogelberg Biosphere Reserve fynbos soil was clustered with SEED database functional assignments of the 12 previously published metaviromes from both similar and dissimilar environments . Open soil samples were collected aseptically during the winter of 2014. Approximately 20 kg of soil was collected at depth of 0–4 cm. Soil samples were stored in sterile containers at −80 °C.70 with some modifications. 8 kg of soil and 1X SM buffer (8 L)  were mixed and shaken vigorously in a sterile container until soil was well suspended and left overnight at 4 °C to settle. The supernatant was centrifuged at 10000 g for 15 min to pellet any remaining soil particles and other debris and passed through a 0.22 µm filter . The filtrate was treated with DNase. Viral particles were precipitated with 10% (w/v) polyethylene glycol (PEG) 8000 overnight at 4 °C and centrifuged for 15 min at 11000 g. After removing the supernatant the viral pellet was resuspended in TE buffer, pH 7.670.Samples were collected in the open soil. Only 3 samples were collected. The DNA of these samples where pooled together for NGS sequencing. Soil samples were processed as previously described71.The absence of bacterial and eukaryotic DNA was confirmed by PCR with primers pairs E9F (5′-GAG TTT GAT CCT GGC TCA G-3′) and U1510R (5′-GGT TAC CTT GTT ACG ACT T-3′) and ITS1 (5′- TCCGTAGGT GAACCTGCGG-3′) and ITS4 (5′- TCCTCCGCTTATTGATATGC-3′)72. The suspension was allowed to dry on the grid, which was then negatively stained with 2% uranyl acetate. Excess stain was removed using filter paper and allowed to air-dry prior to examination using a Philips (FEI) CM100 TEM.Aliquots of viral suspensions isolated from soil were fixed with 2% glutaraldehyde for three hours at 4 °C and 10 µl of the phage suspension was overlaid on a carbon coated grid of 200 MeshTM kit according to manufacturer’s instructions (Zymo Research). Extracted metaviromic DNA (unamplified) was sequenced using an Illumina MiSeq platform . Briefly, following DNA quantification using NanoDrop Fluorospectrometer 3300, 1 ng of isolated metavirome DNA was used to prepare 4 individually indexed NexteraXT libraries. They were then sequenced using the MiSeq v3 (600 cycles) sequencing kit, generating 2 × 300 bp reads. The raw reads were trimmed and demultiplexed, resulting in four fastq files.DNA was extracted from virus particle preparations using a ZR soil microbe DNA MidiPrepThe quality of the raw read files was checked with CLC Genomics Workbench version 6.0.1 . The reds were then filtered and trimmed, with the removal of low quality (sequence limit of 0.05), ambiguous reads . This yielded 1,488,462,918 reads with an average length of 212.05 bp. The post-QC reads were assembled using CLC Genomics Workbench as paired files (3 × 2 read files per site). The assembly resulted in 28,511,204 contigs with a minimum length of 1,002 bases at an N50 of 2,047 and a maximum of 47,854 bases.de novo using CLC Genomics Workbench version 6.0.1 using the default settings. Reads and contigs were uploaded to the MetaVir37 (http://metavir-meb.univ-bpclermont.fr), VIROME (http://virome.dbi.udel.edu/)38 and MG-RAST (http://metagenomics.anl.gov/)39 servers for virus diversity estimations. The viromes were uploaded in 2015 and analysed in 2017. The taxonomic composition was computed from a BLAST comparison with the Refseq complete viral genomes protein sequence database from NCBI (release of 2016-01) using BLASTp with a threshold of 50 on the BLAST bitscore. The assembled sequences were searched for open reading frames (ORFs) and compared to the RefSeq complete viral database using MetaVir and MG-RAST. Functional and organism assignments were based on annotation and other information obtained from the following databases: GenBank, Integrated Microbial Genomes (IMG), Kyoto Encyclopaedia of Genes and Genomes (KEGG), Pathosystems Resource Integration Center (PATRIC), RefSeq, SEED, Swiss-Prot, tremble, and eggnog; and for the assignment of functional hierarchy, COG (clusters of orthologous groups), KEGG Orthology (KO), and NOG databases were used. The Genome relative Abundance and Average Size (GAAS)73 tools were used for normalization of the total composition, estimation of the mean genome length and for the estimation of relative abundance and size for each taxon. The phylogenetic tree were generated by an open-source JavaScript library called jsPhyloSVG74. The phylogenetic trees were based on the reference sequences and the Kogelberg Biosphere Reserve virome sequences, and computed with 100 bootstraps. Further analysis of the sequences was performed using METAGENassist 75. Functional assignments produced by VIROME using 120 identified functional subsystems were used for the statistical analysis with METAGENassist.The processed reads were assembled 76 , and represented as a dendrogram79.Clustering analysis comparison was plotted as a clustering tree and computed with pvclust computed by MetaVir Viral sequences from Kogelberg Biosphere Reserve fynbos soil sample are available on MetaVir under the project KBR under the names “KBR 1 and KBR 2”.Supplementary Information


Strongylocentrotus purpuratus coelomocytes by fluorescence microscopy and flow cytometry. Eight of the lectins  showed distinct binding patterns to fixed and live cells of three major coelomocyte classes: phagocytic cells, red spherule cells, and vibratile cells. Importantly, almost all lectins bound only to a subgroup of cells within each cell type. Lastly, we established fluorescently-labeled lectin-based fluorescence activated cell sorting as a strategy to purify distinct S. purpuratus coelomocyte (sub-)populations based on molecular markers. We anticipate that this will become a routine approach in future studies focused on dissecting the roles of different coelomocytes in echinoderm immunity.Coelomocytes represent the immune cells of echinoderms, but detailed knowledge about their roles during immune responses is very limited. One major challenge for studying coelomocyte biology is the lack of reagents to identify and purify distinct populations defined by objective molecular markers rather than by morphology-based classifications that are subjective at times. Glycosylation patterns are known to differ significantly between cell types in vertebrates, and furthermore they can vary depending on the developmental stage and activation states within a given lineage. Thus fluorescently labeled lectins that recognize distinct glycan structures on cell surface proteins are routinely used to identify discrete cell populations in the vertebrate immune system. Here we now employed a panel of fifteen fluorescently-labeled lectins to determine differences in the glycosylation features on the surface of  Strongylocentrotus purpuratus (purple sea urchin), an echinoderm. Although the S. purpuratus genome sequencing project revealed the existence of hundreds of homologs of vertebrate immune genes, their roles in sea urchin immune responses is only beginning to be uncovered. Coelomocytes are thought to represent the main professional immune cells of sea urchins, and based on their morphological features they can be separated into four distinct types: phagocytes, vibratile cells, red spherule cells, and colorless spherule cells [The immune system of mammals is based on a complex and intricate interplay of large numbers of distinct immune cells types including the B and T lymphocytes that form the cellular basis of adaptive immunity. While a vast body of knowledge has been accumulated about mammalian immunity, far less is known about the properties and roles of different cell types that constitute the potentially almost equally complex defense systems of higher invertebrates like for example le cells . As indile cells , but manIn depth studies of murine and human immune cells were largely facilitated by the development of reagents and tools to distinguish between and to purify different cell types and subpopulations thereof based on molecular markers. Such purified cells allowed subsequent comprehensive studies of their gene expression profiles and their function. Monoclonal antibodies directed against unique cell surface markers represent the most commonly used reagents for identifying individual immune cell types . UnfortuGlycosylation is a common post-translational modification present in extracellular domains of receptor membrane molecules of a wide range or organisms . GlycosyS. purpuratus coelomocytes. We identified several lectins that bind distinct coelomocyte types and/or subpopulations thereof. Furthermore, we demonstrate their suitability for fluorescence microscopy and flow cytometry experiments to separate and purify sea urchin coelomocytes.Based on these observations on vertebrate cells, we here utilized a commercially available panel of fluorescently labeled plant lectins to screen for distinct binding patterns of these molecules to All fluorescently-labeled lectins and the competitors for the lectin binding assay  were obtained from a commercial vendor (Vector Laboratories) .S. purpuratus were originally collected of the California coast, and maintained in sea water at the Academia Sinica ICOB Marine Research Station in Jiaoxi, Taiwan. We obtained all sea urchins from there  and maintained them in artificial sea water  at 14°C. All individuals used for the experiments were apparently healthy, and were kept in our facility for at least 3 month prior to the experiments to minimize influences from environmental changes.3, 0.011 M Na2SO4, 0.03 M EDTA, 0.05 M imidazole) to prevent clotting. Coelomocyte numbers were determined using a hemocytometer.Coelomic fluid was drawn from individual sea urchins using a 1 ml syringe with a 25G×1” gauge needle through the peristomial membrane. The syringe was preloaded with an equal volume of ice-cold calcium and magnesium free sea water containing EDTA and imidazole  to remove non-adherent cells, 100 μls of 4% paraformaldehyde in CMFSW were added, and each sample was fixed for 10 min at room temperature. The excess fixation solution was removed by washing with 3 ml phosphate buffered saline , 100 μl of blocking solution  were added, and incubated for 30 min at room temperature. After washing with 3 ml of PBS, 50 μl microliter of staining solution (PBS containing 1% BSA and 0.5 μg of fluorescein-conjugated lectin or 1 μg of rhodamine-conjugated lectin) were added, and incubated for 1 h at room temperature. Lastly, the slides were washed once with 3 ml PBS, stained with 50 μl 2-(4-Amidinophenyl)-6-indolecarbamidine (DAPI) solution (300 nM in PBS), washed withed 3 ml PBS, mounted with 8 μl 1, 4-Diazobicyclo- mounting medium (2.5% DABCO in 10 mM Tris pH = 7.5 containing 70% glycerol), and coverslips were sealed with nail polish. For the competition assays, α-methylmannoside or N-acetylgalactosamine were added at the staining step to a final concentration of 0.2 M, or chitin hydrolysate solution was added to make up 20% of the final volume.For observing lectin binding patterns on fixed cells, 100 μl aliquots of coelomocyte suspensions were added to poly-L-lysine coated glass slides (Thermo Scientific Superfrost Plus), and allowed to settle down for 30 min at room temperature in a humidified chamber. The slides were washed with 2 ml calcium and magnesium free sea water  and allowed to settle down for 15 min at room temperature in a humidified chamber. After washing the slides with 1 ml of CMFSW-EI, 50 μl of staining solution containing  was added, and the samples were incubated at room temperature in a dark humidified chamber for 30 min. Subsequently, cells were washed once with 1 ml of CMFSW-EI, covered with a coverslip, and immediately observed by microscopy without sealing.To stain coelomocytes in suspension, cells were pelleted by centrifugation at 434×g and the supernatant was discarded to remove glycosylated proteins present in the coelomic fluid. Subsequently, the coelomocytes were resuspended in the same volume of CMFSW-EI, and separated into aliquots of 100–200 μl in volume. Then individual fluorescently labeled lectins were added  and incubated for 30 min on ice in the dark. To remove the staining solution, cells were spun down again at 434×g for 5 min at 4°C, resuspended in the same volume of CMFSW-EI, and 10 μl of the suspension was added to uncoated microscopy slides. Lastly, the cells were covered coverslips, and immediately observed by microscopy without sealing.All slides were observed using a Zeiss Axioimager.Z2 microscope with an Apotome.2 structured illumination accessory. Color images were taken using a digital SLR camera (Canon) attached to an optical port, and fluorescence images were taken using a cooled CCD camera. Raw image files were processed using the Zeiss AxioVision software.To remove glycosylated proteins present in the coelomic fluid, coelomocytes were spun down at 434×g for 5 min at 4°C, resuspended in the same volume of CMFSW-EI, and separated into 100 μl aliquots. Individual fluorescence-labeled lectins  or pairs thereof were added, and cells were incubated for 30 min on ice in the dark. Stained cells were washed once with 500 μl CMFSW-EI, resuspended in 300 μl CMFSW-EI and subjected to flow cytometry on a FACScalibur flow cytometer (Becton Dickinson) using PBS as the sheath fluid. For the competition assays, α-methylmannoside or N-acetylgalactosamine were added at the staining step to a final concentration of 0.2 M, or chitin hydrolysate solution was added to make up 20% of the final volume.To sort coelomocytes, 1 ml of a 1:1 mix of coelomic fluid and CMFSW-EI were pelleted, resuspended in 1.5 ml and stained with LCA-rhodamine and DSL-fluorescein  for 30 min on ice in the dark. Subsequently, the cells were washed with 2.5 ml of CMFSW-EI, and pelleted by centrifugation with 434×g for 5 min at 4°C. After resuspending the cells in 1 ml of CMFSW-EI, individual populations were sorted based on their fluorescence profile into 500 μl EasyPure Total RNA reagent (BIOMAN) using a FACS Aria II flow cytometer in the Core Instrument Center of Chang Gung University College of Medicine.RNA was purified using EasyPure Total reagent (BIOMAN) using 10 μg of glycogen (Roche) as a carrier according to the manufacturer’s protocol. Approximately 150 ng of RNA were converted into cDNA using the ToolsQuant II Fast RT Kit (BIOTOOLS) kit with random hexamer primers according to the manufacturer’s instructions.Sp-Rpl39) in each sample.Gene expression levels were quantified by qPCR using the FAST SYBR green Master Mix (Applied Biosystems) and gene specific primers  in an ABS. purpuratus. This includes the SpTrf (previously refered to as Sp185/333) protein family that is expressed in is distinct types of phagocytic cells but not in spherule or vibratile cells [S. purpuratus coelomocytes carry distinct glycosylation patterns that can be recognized by different lectins, we selected a test panel of fifteen commercially available lectins that were covalently coupled to either fluorescein or rhodamine, respectively  and side scatter (SSC–correlated with cell granularity), revealed a broad distribution within the entire coelomocyte set  overlap with the largest population discernible in the FSC/SSC plot (“red”). This is in agreement with both, the fluorescence microscopy data  do largely overlap with the “yellow” FSC/SSC population and some of them  do also contribute to a varying extend with a “blue” FSC/SSC profile. Lastly, DSL+LCA-, DSL+PSA-, STL+sWGA+, STL+LCA-, and STL+PSA- coelomocytes are unique to the “blue” FSC/SSC population. Combined with the absence of any lectin staining for vibratile cells in the microscopy experiments, we conclude that the “yellow” population and the majority of the double negative cells represent the vibratile cells. Thus the “blue” population likely contains the majority of red spherule cells, and the observation that these cells can be STL+ or sWGA+, but LCA- and PSA- , but there was at least one notable exception: the DSL+LCA- population in sea urchin A  were separated by flow cytometry using appropriate gates (Sp-B7L3) and SPU_015358 (Sp-Egr) (phagocyte-specific), SPU_002895 (Sp-PKS1) and SPU_014528 (Sp-Giant) (red spherule cell-specific), and SPU_019489 (Sp-P2rx4) and SPU_027969 (Sp-FoxJ1) (specific for a mixed population of vibratile and colorless spherule cells). To account for the differences in the numbers of cells collected, all expression values were normalized to that of Sp-Rpl39 for each population. The genes that are preferentially expressed in the DSL+LCA+ population are the phagocyte markers Sp-B7L3 and Sp-Egr consistent with our earlier assignment of this population to be phagocytes based on fluorescence microscopy and analytical flow cytometry data  correlates well with the lectin staining patterns observed in the microscopy and analytical flow cytometry experiments described above. In summary, these results indicate that fluorescently labeled lectins can be used purify different coelomocyte types and subpopulations thereof by flow cytometry, and corresponding RNA preparations are suitable to establish the gene expression profiles of these cells.To test whether fluorescence based cell sorting can be used to purify coelomocyte populations based on their lectin binding properties, fluorescein-coupled DSL and rhodamine-coupled LCA were employed to stain the total pool of coelomocytes from two individual sea urchins . This combination showed four distinct populations in our analytical flow cytometry, and now these four different populations  biological functions. Each cell type exhibited defined lectin binding patterns which corresponds to distinct glycosylation patterns of their cell surface proteins, and this in turn is controlled by glycosyltransferase activities that are linked to the biological function and state of each cell. The precise glycosylation features recognized by each lectin are only beginning to be accurately defined [Paracentrotus lividus, a sea urchin, was recently analyzed by mass spectroscopy, and they confirmed the presence of sialic acid on these cells using fluorescently-labelled sWGA [The four main coelomocytes within  defined . Hence iled sWGA . Our resled sWGA .S. purpuratus larvae two morphologically identical pigment cell subtypes that differ in their gene expression profiles have been described [+ and STL+ cells for at least two coelomocyte types in the flow cytometry experiment could reflect such a common activation marker. In addition, genetic differences between each sea urchin, and differences in their disease history and current immune status could also contribute to differences in lectin binding profiles. Performing lectin staining studies on cells from a large number of individual sea urchins including infection experiments will help to distinguish between shared constitutive glycosylation patterns defining cellular identify, and those that are inducible. As molecular features and markers that correlate to activation states, developmental stages, and coelomocyte subtypes emerge from future studies of echinoderm immunity, these currently seemingly non-consistent staining patterns will likely be resolved.Some of the lectins were found to bind to all cells of a given type  in all individual sea urchin tested, and hence the respective glycosylation features are important for the function of all cells of this type. Other lectins (e.g. PSA), however, differed in their staining pattern within or between individuals . They eiescribed , and it escribed . The preS. purpuratus, the vibratile cells were unique in their inability of being recognized in their native state by any of the fifteen lectins used in this study , while fixed vibratile cells revealed the presence of diverse glycosylation patterns in intracellular compartments. It is tempting to speculate that these are linked to proteins that will be secreted from those cells upon activation, and a role of these cells in clotting consistent with such secretory processes has been discussed in the literature [While we were not able to define any lectin binding profile for colorless spherule cells due to their low abundance in the coelomic cavity of adult terature .S. purpuratus immune cell populations beyond the level of their morphologies. This will set the stage for detailed studies of their properties, development and function during immune responses that are currently impossible to conduct. Importantly, a recent flow cytometric analyses of earthworm coelomocytes included lectins to distinguish cell populations [The flow cytometry experiments strongly suggest that an appropriate combination of FSC/SSC gating combined with appropriate fluorescently labeled lectins should enable us to purify homogenous coelomocyte population for subsequent functional studies and the assessment of their gene expression profiles. The FSC/SSC profiles are relatively coarse measures of cell morphology that are overlapping, and this is likely reflected in the very large but not complete overlap of cell populations defined by these physical features and the molecular properties of lectin binding and gene expression. An iterative process in which increased cell purities will lead to the identification of better molecular markers that will in turn could be used to obtain higher cell purities will resolve some of the apparent inconsistencies observed in our study. One important next step will be using lectin-based cell purification to identify candidate genes that encode cell surface markers for exclusive to unique coelomocyte populations, and to subsequently develop appropriate monoclonal antibody reagents. Overall, we predict that the study presented here will pave the way towards using combination of lectins and antibodies to facilitate the dissection of the ulations , highligS1 FigA+B) Total coelomocytes were directly settled on glass slides, or (C) first separated over a density gradient to obtain cell fractions enriched for phagocytes (ph), vibratile cells (v), and red spherule cells (rs). Cells were fixed with paraformaldehyde, and stained with DAPI and the indicated lectins that were labeled with rhodamine. Representative images were taken on a Zeiss Axioimager.Z2 microscope with a cooled CCD camera using (A+B) a Plan-Apochromat 40x objective, or (C) an Apotome.2 structured illumination accessory and a Plan-Apochromat 40x objective. Respective phase contrast images were taken (without the Apotome.2 feature) to confirm the identity of each cell. The images for the fluorescent channels are shown individually and merged.The lectin staining patterns shown here were not consistent among coelomocytes from all individuals tested as each was only observed in one sea urchin but not in at least two other individuals. ((TIF)Click here for additional data file.S2 FigA-C) Density gradient purified coelomocytes  were settled and glass slides, fixed with paraformaldehyde, and stained with DAPI. (D-G) Total live coelomocytes were settled or added to glass slides and handled according to ((TIF)Click here for additional data file.S3 FigA-D) rhodamine or (E-H) fluorescein in the presence of chitin hydrolysate (ch) or N-acetylgalactosamine (N-ag). Representative images were taken on a Zeiss Axioimager.Z2 microscope with an Apotome.2 structured illumination accessory using a Plan-Apochromat 40x objective and a cooled CCD camera. The exposure times were identical to those used for the respective stained coelomocytes in Total coelomocytes were separated over a density gradient to obtain cell fractions enriched for phagocytes (ph), vibratile cells (v), and red spherule cells (rs). Cells were settled on glass slides, fixed with paraformaldehyde, and stained with DAPI and the indicated lectins that were labeled with ((TIF)Click here for additional data file.S4 Fig(A) Histogram plots of live coelomocytes that were either unstained (red), stained with the indicated fluorescently labelled lectins (blue), or stained with the indicated fluorescently labelled lectin in the presence of the indicated competitors (green). The data from each of the three samples is shown as an overlay. The cells for this dataset were obtained from four individual sea urchins.(TIF)Click here for additional data file.S5 FigA) Total coelomocytes from sea urchin A were stained with the indicated combinations of fluorescently labeled lectins, and analyzed by flow cytometry. The forward/side scatter profiles of each gated population are shown and gates corresponding to the distinct populations (shown in B) Total coelomocytes from sea urchin B were stained with DSL-fluorescein and LCA-rhodamine. The forward/side scatter profiles of each gated population are shown as in (A).(shown in  are show(TIF)Click here for additional data file.S6 FigA) were gated based on their forward/side scatter profile, and four different populations (B) were sorted based on their distinct fluorescence profiles. (C) The forward/side scatter profiles of each indicated population (red dots) was overlaid on that of all cells in the sample (gray dots).Total coelomocytes from sea urchin C were stained with DSL-fluorescein and LCA-rhodamine. Live cells ((TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.