Liver cancer (LC) is one of the most common cancers and represents the third highest cause of cancer-related deaths worldwide. Extracellular vesicle (EVs) cargoes, which are selectively enriched in RNA, offer great promise for the diagnosis, prognosis and treatment of LC. Our study analyzed the RNA cargoes of EVs derived from 4 liver-cancer cell lines: HuH7, Hep3B, HepG2 (hepato-cellular carcinoma) and HuH6 (hepatoblastoma), generating two different sets of sequencing libraries for each. One library was size-selected for small RNAs and the other targeted the whole transcriptome. Here are reported genome wide data of the expression level of coding and non-coding transcripts, microRNAs, isomiRs and snoRNAs providing the first comprehensive overview of the extracellular-vesicle RNA cargo released from LC cell lines. The EV-RNA expression profiles of the four liver cancer cell lines share a similar background, but cell-specific features clearly emerge showing the marked heterogeneity of the EV-cargo among the individual cell lines, evident both for the coding and non-coding RNA species. Human liver cancer (LC) is among the most common forms of cancer and has a dismal clinical outcome, accounting for the third highest cause of cancer-related deaths worldwide . The sevNon-coding (nc)RNA is a functional RNA molecule that is not translated into a protein. Accumulating findings have demonstrated that many ncRNAs such as microRNAs (miRNAs) and small nucleolar (sno)RNAs play diverse biological regulatory functions in many life events and are implicated in cancer progression , 6. It iRecently, small (nanosized) extracellular vesicles (EVs) have emerged as novel entities, which play a fascinating role in cancer progression and therapy, including liver cancer -19. EVs In this study, we used RNA-seq to provide the first comprehensive overview of the expression profiles of coding and non-coding transcripts, microRNAs, isomiRs and snoRNAs carried by the EVs derived from 4 different human liver-cancer cell (LCC)-lines. Form our data clearly emerges, together with certain shared characteristics, the heterogeneity across the 4 cell-lines of the small EVs RNA cargoes, evident from the disparity of the miRNAs, isomiRs, snoRNAs and gene expression profiles.In order to obtain a comprehensive picture of the RNA types transported by liver cancer cell-derived EVs, we isolated small EVs from the conditioned media of four liver cancer cell-lines using a previously published and validated sequential centrifugation protocol . These sEV morphological properties and size distribution were also investigated by atomic force microscopy (AFM). Figure 10 EVs/μl, whereas the Hep3B-EVs was the lower, with about 30% less EVs/μl A quantitative estimation of the molar concentration of EVs Figure  was obtaFinally, the four EV samples were analyzed for the presence of specific EV biomarkers by Western blot. Figure To identify the main species of RNA contained in the EVs derived from liver cancer cells, total RNA was extracted from each EV sample. These RNAs were used to generate two different sets of sequencing libraries: one library was size selected to be enriched for small RNAs  and the other was prepared for the whole transcriptome (WTA library). For the WTA libraries, reads mapped to the human genome (GRCh38/hg38) include ribosomal RNA sequences, LINE and SINE repeated sequences and specific gene transcripts, with the exclusion of miRNAs . We seleFigure It is also noteworthy that many of the highly represented transcripts, both coding and non-coding, are snoRNA host-genes , thus arising the question whether the vesicles contain the complete transcripts or only their relevant snoRNAs. To answer this question and to validate some of these findings a different RNA measuring technique, the RT-qPCR, was used on total RNA derived from EV collected from cell medium and cells bodies of parallel cell cultures.Figure For the study of the miRNA populations contained in the EVs secreted by each liver cancer cell line, we generated small-RNA sequencing libraries starting from total RNA extracted from the EVs released in the growth medium. The libraries were size selected to be enriched for the miRNA fraction and then sequenced on the SOLiD 5500xl platform. After excluding low-quality reads and trimming adaptor sequences, the remaining reads were first mapped to the human genome (GRCh38/hg38) and then to miRbase (v. 20), to annotate known miRNAs in each library. The metrics and the results of this procedure for all the samples are reported in An average expression level of 0.05% in at least one cell line was taken as a threshold to exclude poorly-expressed miRNAs. Using this threshold level, we identified a total of 167 miRNAs in the EVs across all the LCC-lines analyzed .To compare and visualize the miRNA transcriptomes of EVs produced from liver-cancer cell-lines, we performed a hierarchical cluster analysis. As shown in Figure To clearly describe what makes the different EV-types unique in their miRNA content, in Figure High amounts of these four following miRNAs were present in all EVs except those derived from the HuH6 cell-line: miR-19b-3p; miR-17-5p; miR-192-5p; and miR 23a-3p. As noted above, the HuH6 EVs carried the most specific miRNA load, missing or carrying at lower concentration some miRNA particularly abundant in the EVs of other cells, but showing several uniquely enriched miRNAs as follows: miR-372-3p; miR-371a-3p; miR-371a-5p; miR-373-3p; miR-34a-3p and miR-122-5pThe EV-cargos did show some specificity with the detection of miRNAs expressed at high levels in only one line: miR-16-5p in HuH7-EVs only; miR-18a-5p and miR-20a-5p in Hep3B-EVs only and miR-451a in HepG2-EVs only.The expression data obtained by RNA-seq of some of the miRNAs were validated by using RT-qPCR on parallel batches of total RNA derived from LCC EVs and whole cells. The analysis of the cellular RNA was performed to see how similar were the EV-miRNA and the cellular-miRNA expression profiles. Figure More interesting are the results concerning the accumulation of the same six miRNAs in the cells producing the EVs Figure . For mosMost miRNAs comprise multiple sequence isoforms (termed isomiRs) , 28, 29.By applying the procedure described in detail in Material and Methods, a total of 6,953 different isomiRs were identified in the EVs of the four cell lines. Of those, 421 were expressed at a level greater than 0.05% at least in one LCC line and are reported in the We focused our attention on the isomiRs of the 10 most abundant canonical miRNAs for each cell line, as listed in the previous paragraph and reported in Figure Since the de-regulation of snoRNA expression is increasingly linked to cancer , we deteIn Figure The two types of libraries produced very different results. The 20 most abundant snoRNAs for each cell line, detected by the WTA libraries, account for a total of 38 species, 22 belonging to the H/ACA box type, 12 to the C/D box type, and only 4 to the Small Cajal body-specific RNAs (scaRNA). On the other side, their counterparts from the small RNA libraries account for a total of 41 species, 30 belonging to the C/D box type, only 6 to the H/ACA box type and 5 of the scaRNA type.SNORA73B, SNORA73A, SNORA63 were well represented in all the EVs according the data from the WTA libraries, and are known to be among the most abundant snoRNAs in mammalian cells. Widely present were also SNORD26, SNORD22, SNORA48 and SNORD100. Again, the HuH6 EVs carried a cargo of snoRNA most different from the other cell lines, with many snoRNAs, as SNORA61, SNORD38A and SNORD95, expressed at higher level only in the EVs from this cell line. The snoRNAs detected in the small RNA libraries were only partially overlapping with those identified in the WTA libraries. Most of snoRNAs detected in small RNA libraries, as SNORD97, were expressed at high level only in these libraries.Previous studies have demonstrated that the hepatoblastoma-like (HuH6) and the hepatocellular-carcinoma-like  cancer cell-lines maintain the hepatocarcinogenic phenotype at gene, miRNA, and protein expression levels, and are useful to gain new insights into the pathogenesis of hepatoblastoma and hepatocellular carcinoma, providing novel biomarkers , 21.The present study represents a detailed analysis of all the coding and non-coding transcripts carried by EVs derived from 4 LCC-lines, profiling gene expression through RNA-seq, and identifying large RNAs, microRNAs, isomiRs, and snoRNAs. To our knowledge, only one previous study characterized the EVs large RNA content derived from three different HCC cell lines  using NGBiophysical analysis indicates that the EV populations have comparable physical properties, including morphology and size distribution. Our study also demonstrated that membrane composition and EV-cargo content differ across the 4 LCC-line-derived EV-populations, confirming several previous studies which have demonstrated that EV-membrane composition and cargo content differ greatly, depend on cell-type, and are usually regulated by it , 33.We demonstrate the purity of the isolated EVs by western blot, excluding contamination by other membrane fragments. The western blots revealed the presence of EpCAM in all EVs and, to a greater extent, in Hep-3B and HepG2-EVs. EpCAM is a “stem-associated” marker and has been linked to poor outcome in HCC , suggestThe size-distribution of the RNA cargo of all the LCC-EVs, spanning from 25 up to 4000 nt, is well in accord with that reported in previous studies . The traThe abundance in all EVs of vault RNAs is puzzling but has already been reported , 41. TheAmong the lncRNAs, H19 is the most documented in oncogenesis and aberrantly expressed in multiple malignancies and its expression levels correlate with recurrence, metastasis, and patient survival. Its presence in HCC-EVs has already been described , 43. H19miRNA-analysis of the LCC-derived EV cargoes showed that some miRNAs were abundantly present in the EVs secreted from all cell lines, while certain other miRNAs were only abundant in the EV derived from one cell line. The most abundant commonly-shared miRNAs were known oncomiRs such as miR-21 , membersOnly the HuH6-derived EV cargoes contained abundant levels of miR-372-3p, miR-371a-3p, miR-371a-5p and miR-373-3p. Since the miR-371/372/373 cluster has been identified as being specific to “human embryonic stem cells” (hESCs), these miRNAs are directly associated with embryonic carcinomas -57. HB iThe expression data, produced by RNA-seq, of a specific set of EV-miRNAs has been validated by RT-qPCR, obtaining only a partial consensus between the measurements as reported in the Results section. More interesting, for the same set of miRNAs, the expression level in the EVs has been compared with that in the cells from which the vesicles originated. In general, apart from some slight variation, miRNA expression amount in EV-cargoes mirrored miRNA expression level in the source cell-line, except for miR-451a. This miRNA was present in all the LCC-EVs, but was undetectable in the LCC-lines, thus indicating the existence, at least for some miRNA, of a very efficient and selective EV-loading mechanism. miR-451a is encoded by a gene located on chromosome 17. It is already known that miR-451a acts as a tumor suppressor, down-regulated in many tumors, including LC , 63. It The miRNA sequence diversity indicated that a range of variants were expressed in the EVs derived from the LCC cell lines, showing different and often composite sequence alterations. As far as isomiR ends are concerned, in conformity with previous studies , 66, 67,Along with miRNAs, snoRNAs were the most highly-represented class of non-coding RNA in all the LCC-EVs. snoRNAs play important roles in the maturation of rRNA, tRNA, snRNA as well as in mRNA biogenesis . snoRNAsMany studies have proposed that fragments of full-length ncRNAs could acquire new functions , 74, andThe study of the biological relevance of EVs in liver-cancer development and progression represents a research field in rapid growth , 19 and The following liver cancer-derived cell-lines were used in this study: HepG2, Hep3B, , HuH-7, HuH6 clone 5 . HuH7, Hep3B and HuH6 cells were grown in Dulbecco’s Modified Eagle Medium (DMEM)  while HepG2 cells were cultured in Eagle’s Minimum Essential Medium (EMEM) (Life Technologies). All media were supplemented with 10% fetal bovine serum (FBS) (Life Technologies), 1% l-glutamine, 1% penicillin/streptomycin , in a 5% CO2-humidified chamber at 37°C.FBS and human serum albumin (hBSA) solution (Life Technologies) used for EV production were depleted from endogenous EVs prior to use by ultracentrifugation at 120,000 g for 5 hours, using an Ultracentrifuge Optima L-100K Ultracentrifuge . Afetr centrifugation, the FBS and hBSA supernatants were filtered with a 0.22 μm filter  and stored in aliquots at -80°C.6 cells/mL) were washed 2 times with PBS (Life Technologies), then incubated for 24 hours in DMEM/F12 (1:1) (Life Technologies) supplemented with 1% EV-free FBS and 0.25% EV-free hBSA at 37°C and 5% CO2. Cell viability was assessed using trypan blue exclusion methods. Presence of apoptotic cells were checked by flow-cytometric assay for Annexin-V expression. EVs were prepared from the cell-culture media using differential centrifugation steps as previously described with some modification [HuH7, Hep3B, HepG2 and HuH6 80%-confluent cell plates (1-2 ×10fication . All preSynthetic phosphatidylcholine (PCh) liposomes were prepared as previously described . Briefly2O with protease inhibitors (1:1000), diluted 1:12,5 with deionized H2O and mixed with a final concentration of 3 nM AuNPs (15 nm). The blue shift was quantified by collecting the UV-Vis spectra of the different AuNP-EVs solutions. UV-Vis spectra were measured with an EnSight multimode plate reader (PerkinElmer) spectrophotometer and acquired with 1 nm step size in a wavelength window ranging from 400 nm to 900 nm. The AuNPs aggregation index (AI) was defined as the ratio of the LSPR absorption at 519 and 650 nm (AI = A519/A650).EV preparations were checked for purity using a colorimetric nanoplasmonic assay developed by Maiolo et al. , 78. TheLiposomes and EVs were fluorescently labeled with 2--1-Hexadecanoyl-sn-Glycero-3-Phosphocholine (BODIPY FL C5-HPC), a highly fluorescent lipid probe previously dissolved in ethanol up to a final concentration of 0,01 mg/mL. Briefly, 5 μL of BODIPY FL C5-HPC has been dried in a 1,5 mL Eppendorf. Then 90 μl of resuspended EVs preparations were added and incubated for 2 hours at room temperature under constant rotation. Finally, exosome labeled preparations were centrifuged at 100,000 × g for 2 h.Liposomes and EVs were labeled with BODIPY FL C5-HPC membrane dye as described above. EVs enriched pellet were resuspended in 10 μL of TAE  plus 0.02% SDS and then loaded on a 0.6% agarose gel and electrophoresed 30 min at 100 V. Fluorescent signal was acquired using a G:Box Chemi XT Imaging system (Syngene). Then the gel was stained with Coomassie Brilliant Blue for 30 minutes at room temperature and destained in 10% acetic acid, 20% methanol overnight. Images were acquired using a G:Box Chemi XT Imaging system (Syngene).Each EV sample was diluted 1:100 with deionized water. Five to 10 μL of samples were then spotted onto freshly cleaved round shaped mica sheets . Mica substrates were dried at room temperature and analyzed using a NANOSURF NAIO AFM, equipped with Budget Sensors AFM tips (Multi75GD-G). Images were snapped in light tapping mode; scan size ranged from 1 to 25 μm and scan speed ranged from 0.8 to 1.2 ms x clock .EVs size distribution analysis was performed with WSxM 5.0 software as previously published . BrieflyProteins were isolated from HuH7, Hep3B, HepG2 and HuH6 cells and from EVs derived from the same liver-cancer cell-lines using M-PER Mammalian protein extraction reagent  supplemented with 1% of Halt Protease and the EDTA-free, phosphatase-inhibitor cocktail  and 1% of EDTA solution , according to the manufacturer’s indication. The isolated proteins were stored at -20°C. The concentration of total protein preparations was quantified by the BCA assay .Cells and EV lysates (10 μg) were electrophoresed and transferred to nitrocellulose membranes. Membranes were then blocked in 5% non-fat milk or 5% BSA, 10 mM Tris-HCl pH 7.5, 100 mM NaCl, 0.1% Tween-20, and probed with the following primary antibodies : anti-Hsp70, anti-Calnexin, anti-GM130, anti-CD9, anti-TGM2 (D11A6), anti-EpCAM (D1B3) and anti-E-cadherin all purchased from Cell Signaling Technology ; anti-CD63 and anti-β-actin purchased from Sigma-Aldrich ; anti-LGR5 (-GPCR GPR49) purchased from ABCAM ; and incubated in the presence of specific horseradish-peroxidase conjugated IgG. Immunoreactive bands were identified using the ECL detection system .Total RNA was extracted from EVs prepared as described above using Fatty Tissue RNA Purification Kit  following the manufacturer’s protocol. For each cell line, two independent biological replicates were used for RNA preparation. Quality, yield and size of the EV RNA were analyzed using capillary electrophoresis, with both Agilent RNA 6000 Pico Kit and Agilent Small RNA Kit on an Agilent 2100 Bioanalyzer . Total RNA was extracted from cultured LCC cells lines using the Fatty Tissue RNA Purification Kit  following the manufacturer’s protocol. RNA quality was checked by analysis on Agilent Bioanalyzer using the Agilent RNA 6000 Nano Kit.Library preparation, sequencing and bioinformatic analysis were done by the service provider GENOMNIA srl . For each RNA sample, two different libraries were generated, one to analyze small RNA and the other larger RNA. Small RNA libraries were prepared directly from total RNA samples without any RNA selection using the small RNA protocol of the SOLiD® Total RNA-Seq Kit, consisting in directional SOLiD adapter ligation, retrotranscription and barcoding through PCR amplification. The libraries were quantified with the Bioanalyzer see  and thenWTA libraries were prepared starting from the same total RNA samples using the WTA protocol of the SOLiD® Total RNA-Seq Kit. The RNA was first fragmented by mild alkaline hydrolysis, then after ligation of the directional SOLiD adapter, was retrotranscribed and barcoded through PCR amplification. The libraries were quantified with the Bioanalyzer see , then poTo obtain absolute quantification of gene expression, the colorspace sequencing files produced by sequencing the WTA libraries were mapped against human genome GRCh38/hg38 using Lifescope software (ver. 2.5.1) in single-ended mode. Each Ensembl Gene ID (release 81) was then assigned an expression value representing the number of mapped sequences. These counts were then normalized and used to perform differential analysis using the R EdgeR package (version 3.2.1) and Genomnia analytical parameters. Then to each Ensembl Gene ID a Gene Name and Gene type have been associated by using Ensembl BiomaRt software. The Gene Type was used to identify the different categories of genes quantified in this study. To determine the miRNA expression profiles, the data files obtained by sequencing the small RNA libraries were analyzed by the Lifescope software using the “small RNA” pipeline and mapped against the human genome GRCh38/hg38 and the miRBase (version 21) dataset.For the large transcript analysis total RNA was reverse-transcribed with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the manufacturer’s instructions, using a maximum of 100 ng of total RNA for each 10 μL of reaction final volume. cDNA aliquots equivalent to 1 ng of RNA were then subjected to real time PCR analysis with an Applied Biosystems 7900HT thermal cycler using the TaqMan® Gene Expression Master Mix (Applied Biosystems) and the TaqMan® Gene Expression Assays (Applied Biosystems) for the following genes: VTRNA1-1, H19, EEF2, RACK1 (GNB2L1), SNHG12, SNHG1. The experiments were performed using biological duplicates and each measurement was performed in triplicate.For the analysis of miRNA expression, 10 ng of total RNA was reverse-transcribed with the TaqMan Advanced miRNA cDNA Synthesis Kit (Applied Biosystems) according to the manufacturer’s instructions. Equal amounts of cDNA (corresponding to 10 pg of RNA) were then subjected to real time PCR analysis with an Applied Biosystems 7900HT thermal cycler using the Fast Advanced Master Mix (Applied Biosystems) and the TaqMan® Advanced miRNA Assays for the following microRNAs: hsa-miR-92a-3p, hsa-miR-93-5p, hsa-miR-17-5p, hsa-miR-451a, hsa-miR-21-5p, hsa-miR-373. The experiments were performed using biological duplicates and each measurement was performed in triplicate.The data were analyzed by the Applied Biosystems SDS software v4.0 and the deltaCt were plotted and used to compare specific RNA and miRNA abundance.


The distributions of socioeconomic status (SES) factors have been changing in Japan. We examined the relationships among SES and self-rated health (SRH) in Japanese adults.We analyzed 1,178 men and 1,555 women. We showed the distribution of SRH by sex and age and examined cross-sectional relationships among educational attainment, marital/living statuses, working status, household income and expenditure, and fine SRH . We adjusted for age, subjective symptoms, visiting doctors, monthly equivalent household expenditure (EHE), and living in their own house.The age-standardized prevalence of fine SRH was 79% and 73% among men and women, respectively. Among men, graduating from high school  and university or junior college  was associated with fine SRH. Among women, graduating from university or junior college was associated with fine SRH . Neither marital/living status nor working status was associated with SRH after adjustments for age in either sex. Among women, high EHE and income were associated with fine SRH . These simple relationships were not observed for men.High educational attainment was associated with fine SRH. Relationships among household income, EHE, and fine SRH differed by sex. According to the CSLC conducted in June 2010 (CSLC2010), the prevalence of Japanese adults with fine SRH defined as excellent, very good, or good SRH was 74% and 71% among men and women, respectively.4Self-rated health (SRH), a subjective perception of an individual’s overall health, is a powerful predictor of all-cause mortality in general populations.5 Lower educational attainment,6,7 being unmarried,7,8 not working,9,10 and having a low income6,10–13 have been associated with a deteriorated SRH in Japan; however, previous findings are inconsistent.9,14,15Socioeconomic statuses (SESs) are reported as fundamental determinants of human function across the life span.16 The numbers of women and elderly people in the labor force have been growing.17,18 Mean annual household income has been decreasing.19 Marriage rates have also been declining.20 Couples are getting married later and later.20 The average number of members per household has been in a steady decline.21 These changes in SESs may be followed by changes in the class identification, a subjective view of their location in the social structure and their social preferences.22 Since low-grade class identification was reportedly associated with deteriorated SRH in Japan,14 further studies are needed in order to clarify whether SESs are associated with SRH in Japan.The distributions of SESs have been changing in Japan for dozens of years. More individuals have attained a high-level education.In the present study, we examined relationships among educational attainment, marital/living status, working status, household income and expenditure, and SRH using the latest cross-sectional dataset of a representative Japanese general population.23–26A prospective cohort study on cardiovascular diseases entitled the National Integrated Project for Prospective Observation of Non-communicable Disease and its Trends in the Aged 2010 (NIPPON DATA2010), was launched in November 2010, collaborating with the National Health and Nutrition Survey in November 2010 (NHNS2010) and CSLC2010, which were executed by the Ministry of Health, Labour, and Welfare, Japan. The methodology and summary of the findings of the NIPPON DATA2010, NHNS2010, and CSLC2010 have been reported elsewhere in more detail.The participants in the dietary survey for NHNS2010 were 8,815 residents who were aged 1 year and older and from 300 districts randomly selected throughout Japan. Among 7,229 participants aged 20 years or older, 2,898  agreed to participate in the baseline survey for NIPPON DATA2010. In the present study, we integrated the data of NIPPON DATA2010 with those of NHNS2010 and CSLC2010 for 2,807 participants . Based on the information obtained from CSLC, we excluded 74 participants who had been admitted to a hospital or living in a facility at the time of the CSLC2010 survey. We eventually analyzed the data of the remaining 2,733 subjects .All participants gave their informed consent before enrollment. The study plan was approved by the Institutional Review Board of Shiga University of Medical Science .Data on SRH was obtained through a question item, “What is your present general health status?” in the self-reported questionnaire for CSLC2010. The following five options were given: “excellent,” “very good,” “good,” “fair,” and “poor”. Subjects who did not choose any of these options were regarded as returning an invalid response. Subjects were dichotomized according to their responses; those who self-reported “excellent”, “very good”, or “good” were regarded as being in a fine SRH condition, while those who reported “fair” or “poor” or gave an invalid response were regarded as being in a deteriorated SRH condition.In the present study, SES variables included educational attainment , marital/living status , yearly household income , or returning an invalid response; 100 JPY is nearly equivalent to 0.9 US Dollars as of the beginning of May 2017), and monthly equivalent household expenditure  in May 2010 (in quintiles). The above classification was made based on information obtained using self-administered questionnaires for NIPPON DATA2010 , CSLC2010 , and NHNS2010 (household income).Information on whether subjects had any subjective symptoms and were visiting a doctor was obtained through a self-administered questionnaire for CSLC2010. Subjects were asked whether they had any of the following symptoms: fever, tiredness, not sleeping well, feeling irritated, forgetfulness, headaches, dizziness, blurred vision, vision problems, ear buzzing, hearing difficulty, palpitation, breath shortness, chest pain, cough and/or sputum, congested and/or running nose, wheezing, heavy stomach and/or heartburn, diarrhea, constipation, appetite loss, abdominal and/or stomach pain, pain and/or bleeding due to hemorrhoids, tooth pain, swelling of and/or bleeding from dental gums, difficulty biting, rash, itchiness, shoulder stiffness, low back pain, pain at limb joints, difficulty in limb movement, feeling cold at the limbs, swelling and/or tiredness at the foot, difficulty and/or pain in urination, urinary incontinence, menses issues, bone fracture and/or joint injury, cut and/or burn injury, and other symptoms, including those yet to be diagnosed. In addition, subjects were asked whether they were visiting a doctor for any of the following health issues: diabetes; obesity; dyslipidemia; thyroid diseases; depression and/or other mental disorders; Parkinson disease; neurological diseases; vision disorders; hearing disorders; hypertension; stroke; coronary artery diseases; other circulatory diseases; cold; allergic rhinitis; asthma; other respiratory diseases; diseases of the stomach, duodenum, liver, gall bladder, or other digestive organs; dental diseases; atopic dermatitis; other skin disorders; gout; rheumatoid arthritis; arthropathy; shoulder stiffness; low back pain; osteoporosis; renal diseases; prostatic hyperplasia; menopause and post-menopause disorders; bone fracture; other injuries; anemia and/or hematological diseases; cancer; pregnancy and/or obstetric disorders; infertility; and other health issues, including those yet to be diagnosed.27The distribution of SRH conditions was assessed separately by sex and according to 10-year age groups. The Cochran-Armitage test was employed to test linear associations between age and fine SRH. The proportions of fine SRH were age-standardized to the national population of Japan in 2010 .We calculated odds ratios (ORs) and their 95% confidence intervals (CIs) for fine SRH by each SES variable with logistic regression analyses. We initially calculated crude ORs. When examining the relationship between yearly household income and SRH, we adjusted for the square root-transformed number of household members. When examining the relationship between monthly EHE and SRH, we adjusted for whether or not subjects were living in their own house because EHE included household rent but not a mortgage. After calculating age-adjusted ORs, we constructed two multivariable models, models 1 and 2. In model 1, we adjusted for age, having any subjective symptoms, and visiting a doctor. In model 2, we adjusted for monthly EHE and living in their own house, in addition to the factors in model 1. In order to assist in the interpretation of relationships among each SES variable and fine SRH, we also examined the relationships among age and each SES variable using the chi-squared test separately by sex.Statistical calculations were performed using IBM SPSS Statistics 24 for Windows . The level of significance was 0.05 (two-tailed) for all tests. Subjects with missing responses were excluded from the corresponding analyses.P for trend <0.001). The age-standardized prevalence of fine SRH was 79% in men and 73% in women.The prevalence of each SRH category is presented separately by sex and age in Table th highest quintile of EHE showed an association with fine SRH relative to those at the lowest quintile.Educational attainment was positively associated with SRH Table . A bivarth and 5th highest quintile) monthly EHE was significantly associated with fine SRH.The relationship between having a high school diploma and fine SRH was significantly attenuated after adjustment for age Table . HoweverSignificant differences were observed in educational attainment, marital/living status, working status, and yearly household income by age in men and women . Age was4 Therefore, the subjects in the present study may be regarded as being representative of the participants of CSLC2010.The age-standardized prevalence of fine SRH was 79% and 73% among men and women, respectively. The present study indicated that the prevalence of fine SRH decreased as subjects aged. These results are consistent with those among all adult participants in CSLC2010.In the present study, a significant association was observed between a younger age and higher educational attainment. This needs to be considered when interpreting results on the relationship between educational attainment and SRH. Among men, the OR for the relationship between educational attainment of high school or higher and fine SRH was attenuated by approximately 30% after adjustments for age, even though it remained significant. On the other hand, in women, only university or junior college diplomas were significantly associated with fine SRH after adjusting for age.6 Meanwhile, Wada et al examined male employees in their fifties and found that lower educational attainment was associated with worse SRH, independent of work-related conditions and marital status.7 In contrast, some research groups failed to find a significant association between educational attainment and SRH.9,14 The strength of the present study is that we adjusted for any subjective symptoms and visiting a doctor in the assessment of the relationship between educational attainment and SRH, which had not been performed in the above-described studies.Previous findings in Japan on the relationship between educational attainment and SRH are inconsistent. Honjo et al also reported that, relative to an 11-year or shorter educational duration, a 13-year or longer educational duration was associated with a lower prevalence of poor self-rated physical health in women only, after adjustments for age, gender, and marital status.Men who were single and were not living alone appeared to have better SRH than those who were married, while women who were single and were living alone appeared to have worse SRH. These relationships diminished after age adjustments. In the present study, most men who were single and were not living alone were young, ranging from 20–49 years old. Most women who were single and were living alone were aged 60 or older. Age is considered to be a major confounding factor in the relationship between marital/living status and SRH.7 We did not obtain information on the human relationships of the subjects with their spouse and family, which may be a health determinant. Chung and Kim reported that satisfaction in marriage was associated with fine SRH in Japan, independent of sex, age, educational attainment, employment, self-rated social class, and religion.15Further studies are needed in order to clarify whether marital/living status is related to SRH independent of age and other confounding factors. In a study by Wada et al, in which subjects were Japanese male employees aged between 50 and 59 years, married men had better SRH than unmarried men independent of educational attainment and the types of occupations and employment contracts.Men and women who were working appeared to self-rate their health statuses as better than those who were not. However, these relationships vanished following age adjustments. The younger the subjects were in the present study, the more frequently they were working. Therefore, this relationship may merely be a result of an age confounder.9 Wada et al showed that middle-aged male employees in manufacturing were more likely to experience the worsening of their SRH, independent of educational attainment and marital status, than those in management.7 They also reported that precarious employment contracts were associated with worsening SRH.7 Further studies are needed in order to clarify the relationship between work-related variables and SRH.On the other hand, previous studies implied that different findings may have been observed if another work-related variable, such as occupation contents or work contracts, had been used to classify subjects. For example, Furuya et al reported that the employed were more likely to have good SRH than the unemployed among community dwellers, even after adjustments for gender, age, educational attainment, and household income.6 Fukuda and Hiyoshi reported that, in women, lower EHE was associated with cardiovascular risk factors, such as obesity, hypertension, diabetes, and the presence of multiple risk factors, while this relationship was not found in men.28 Men generally earn more than women in Japan. The mean monthly paid income of husbands was 422,000 JPY, while that of wives was 136,000 JPY, according to the Family Income and Expenditure Survey of Japan in 2010.29 Thus, husbands likely earned high incomes in high-income households, and the SRH of these husbands may have worsened due to the high burden of work.The relationships among yearly household income, monthly EHE, and SRH differed by sex. In women, a high income and EHE were consistently associated with fine SRH. Meanwhile, in men, the highest income group was not associated with fine SRH after adjustment for EHE. Furthermore, the highest expenditure group was not associated with fine SRH. Other studies also reported the possible effect modification by sex for the relationships among income, EHE, and health in Japan. In a study by Honjo et al, a relationship between a low income and poor self-rated physical and mental health was only found in women.A considerable number of subjects gave invalid responses regarding their household income  and EHE (4.8%). Concerning the household income, we made an independent group of those with an invalid response and included it in statistical analyses. Among women, this group showed a higher prevalence of fine SRH than the lowest income group. In contrast, this relationship was not found in men after adjustments for age. Difficulties may be associated with calculating the household income in a household in which two or more individuals earn an income. Concurrently, some of these households must have earned incomes of 2 million JPY or greater. This may explain the present results showing that women who gave invalid responses regarding their household income reported fine SRH more frequently than those with yearly household incomes of less than 2 million JPY.The present study has the following limitations. We were unable to clarify the causal relationship between SES and SRH because the present results were obtained in a cross-sectional manner. Furthermore, there was a possible selection bias. The present subjects were limited to those who were willing to participate in the study and were not staying in a hospital or living in a care facility. The present results may not be applicable to the general population. Therefore, these results may not be applicable to other countries in which SES and SRH are different from Japan.The age-standardized prevalence of fine SRH was 79% and 73% among men and women, respectively. The older the subjects’ age category, the lower the prevalence of fine SRH. We analyzed relationships among SES and SRH using the latest cross-sectional dataset of a representative Japanese general population. Higher educational attainment was positively associated with SRH. In men, graduating from high school or higher was associated with fine SRH relative to graduating from elementary or junior high school, while, in women, graduating from university or junior college, but not from high school, was associated with fine SRH. The relationships among marital/living status, working status, and SRH were explained by differences in age in the present study. In addition, relationships among yearly household income, monthly EHE, and SRH differed by sex. The highest income and EHE groups were associated with fine SRH in women. However, these simple relationships were not found in men.


Glomeruli are excellent pre-determined natural structures for laser micro-dissection. Compartment-specific glomerular gene expression analysis of formalin-fixed paraffin-embedded renal biopsies could improve research applications. The major challenge for such studies is to obtain good-quality RNA from small amounts of starting material, as applicable for the analysis of glomerular compartments. In this work, we provide data and recommendations for an optimized workflow of glomerular mRNA analysis.With a proper resolution of the camera and screen provided by the next generation of micro-dissection systems, we are able to separate parietal epithelial cells from glomerular tufts. Selected compartment-specific transcripts  seem to be reliable discriminators for these micro-dissected glomerular substructures. Using the phenol–chloroform extraction and hemalaun-stained sections (2 µm), high amounts of Bowman’s capsule transections (> 300) reveal sufficient RNA concentrations (> 300 ng mRNA) for further analysis. For comparison, in unstained sections from a number of 60 glomerular transections upwards, a minimum amount of 157 ng mRNA with a reasonable mRNA purity [A260/A280 ratio of 1.5 (1.4/1.7) median (25th/75th percentiles)] was reversely transcribed into cDNA. Comparing the effect of input RNA , transcript expression of POLR2A significantly correlated when 60 and 150 laser micro-dissected glomerular transections were used for analysis. There was a lower inter-assay coefficient of variability for ADAMTS13, when at least 60 glomerular transections were used. According to the algorithms of geNormPlus and NormFinder, PGK1 and PPIA are more stable glomerular reference transcripts compared to GUSB, GAPDH, POLR2A, RPLPO, TBP, B2M, ACTB, 18SrRNA and HMBS.q values using our suggested reference transcripts (PGK1 and PPIA) allows compensation with respect to different amounts of RNA purity and quantity.Our approach implements compartment-specific glomerular mRNA expression analysis into research applications, even regarding glomerular substructures like parietal epithelial cells. We recommend using of at least 60 micro-dissected unstained glomerular or 300 hemalaun-stained Bowman’s capsule transections to obtain sufficient input mRNA for reproducible results. Hereby, the range of RNA concentrations in 60 micro-dissected glomeruli is low and appropriate normalization of CThe online version of this article (10.1186/s12867-018-0103-x) contains supplementary material, which is available to authorized users. Laser capture micro-dissection (LCM) enables the isolation of single cells or small cell groups from histological sections under direct microscopic control . CombineA comprehensive study for RNA quality and quantity was recent performed for the first time in renal FFPE tissue . FurtherTherefore, one aim of this study was to identify stably-expressed reference transcripts by proper normalization strategies and compare our approach for quantitative mRNA analysis of micro-dissected glomerular compartments with others. Another focus was to illustrate the possibilities for laser micro-dissection of glomerular substructures in detail. In addition, we studied the effect of the amount of micro-dissected glomerular transections for further RNA purity and quantity control, especially the net result for relative quantification. Hereby, we focused on two candidate reference transcripts (GAPDH and POLR2A [polymerase (RNA) II (DNA directed) polypeptide A)] and one target transcript [ADAMTS13 ] due to our interest in thrombotic microangiopathy.Overall, FFPE native and transplant kidney biopsies from 24 patients were selected from the archive of the Institute of Pathology, Hannover Medical School and Institute of Pathology, Department of Nephropathology, Friedrich-Alexander University Erlangen-Nuremberg. (i) Nine native kidney biopsies with acute tubular injury (ATN) or interstitial inflammation without any glomerular disease were selected for the practicability of the micro-dissection of parietal epithelial cells . (ii) In order to determine reference transcripts, we used an additional fifteen patients selected by a high number (> 30) of glomeruli per biopsy, including a wide range of native and transplant biopsies (patient cohort II). These patients had different glomerular, tubulo-interstitial and hypertension-related renal diseases. Eight of these patients were analyzed for the effect of input RNA. Patient characteristics for all biopsies are detailed in Table ® CellCut Plus® Laser-Micro-dissection System, Molecular Machines and Industries (MMI), Eching, Germany and MMI® CellCamera DXA285cF) with the following settings: energy: 70%, focus: 50%, cutting speed: 40%.All biopsies were cut at a thickness of 2 µm. In order to test the practicability of micro-dissection of PECs (patient cohort I), biopsies were deparaffinized for 30 s in xylol, stained for 2 s in hemalaun  and washed in sterile aqua ad injectabilia . After the drying of several consecutive sections, non-sclerotic glomerular tufts were micro-dissected from PECs using a next generation micro-dissection system  with the same laser settings. For reference transcript analysis, 60 glomerular transections from all fifteen patient samples were used. In order to determine the effect of input RNA for valid mRNA expression analysis, 20, 60, 150 and 300 glomerular transections from eight patient samples out of cohort II were used.Alias: Cyclophilin A), ACTB (Beta-Actin), eukaryotic 18S rRNA, B2M (Beta-2-microglobulin), HPRT1 (Hypoxanthine phosphoribosyltransferase 1), RPLPO , TBP (TATA-box binding protein) and HMBS (hydroxymethylbilane synthase)] as well as compartment markers WT1 (Wilms tumor 1) for podocytes/PECs, PAX2 (Paired box 2) for PECs/tubulointerstitium and GLEPP1  for podocytes/PECs are detailed in Table q values (Cq > 35) and missing Cq values were replaced by Cq = 36  are necessary and sufficient for mRNA expression analysis. This number of transections can be reasonably achieved in most routine biopsies.In order to document RNA yields and transection amounts, we used two different approaches. (I) For t et al. , which oE tissue . Especiadeparaffinized and hemalaun-stained Bowman’s capsule transections, we can only provide a rough estimate, because we performed no comprehensive analysis for different amounts of Bowman’s capsule transections. In all samples the RNA concentration was higher than the detection limit of spectrophotometers (10 ng/µl) [(II) For the amount of tometers  ng/µl [10 ng/µl) .In general, one has to keep in mind that concentration estimation can also be affected by phenol contamination, given that phenol absorbs strongly at 230 nm and ~ 270 nm. Indeed, in many samples we had high absorbance at 230 nm (data not shown). Therefore, the A260/A230 ratio was strongly reduced in our samples. However, there is no consensus on the acceptable lower limit of this ratio and the most important factor is the amount of phenol that is transferred to the downstream reaction, rather than the absorbance ratio. It is important to remember that absorbance ratios also depend on RNA concentration, especially in case of laser micro-dissection when RNA is at very low concentrations. Vice versa, absorbance around 260 nm can affect RNA concentration. Therefore, spectrophotometric analysis  of FFPE tissue yield different, consistently higher RNA concentrations compared to fluorometric analysis (e.g. Qubit) .Furthermore, different RNA extraction methods yield different amounts of RNA . We usedTo date, studies on PECs are limited because the small amounts of PECs could not be analyzed by quantitative real-time PCR for mRNAs. Our approach for laser micro-dissection can overcome this limitation. In contrast to all other studies shown in Table q value . In order to avoid missing any low-level expressed transcripts, we suggest the pragmatic approach of replacing all off-scale Cq values (Cq > 35) and missing Cq values by Cq = 36 [Another aspect in case of micro-dissected glomerular transections with small amounts of starting material is how to manage reactions that do not give rise to any C Cq = 36 .For certain projects, it could be relevant to compare gene expression levels between a normal (or less injured) glomerulus and a sclerotic glomerulus in the same biopsy sample. The diameter of a human glomerulus is on average about 150 µm. Therefore, in theory about 75 transections (cut at a thickness of 2 µm) could be cut from one single glomerulus. Indeed, this number of transections could provide sufficient RNA. However, in practice it will be difficult to identify a single glomerulus over multiple section levels. Therefore, it would be an approach to pool glomeruli with normal (or less injured) morphology as well as sclerotic glomeruli. For example, we would suggest micro-dissecting about 20 transections and pooling three glomeruli per biopsy.Twelve different candidate reference transcripts were tested for expression stability. All candidate reference transcripts are located on different chromosomes and are involved in different basic cellular processes, as shown in Table As discussed in Cohen et al. , a consiFurthermore, the number of biopsies for analyzing the effect of input RNA (patient cohort II) is difficult to increase due to the size limit of renal biopsies in clinical practice. However, even in our eight cases POLR2A revealed a reliable reproducibility for different amounts of RNA recovered from 60 to 150 micro-dissected glomerular transections when normalized to PGK1 and PPIA. There may be two reasons for the missing correlation of GAPDH and ADAMTS13 relative expression: (I) the small number of biopsies analyzed; or (II) the lower expression level of GAPDH and ADAMTS13 compared to POLR2A. Consequently, the inverse conclusion might be that fewer values of lower expressed transcripts have to be approached with caution.Another aspect is the use of markers for discrimination between Bowman’s capsules and the tubulointerstitium. Due to the low amount of starting material, we focused on two positive markers being highly expressed in podocytes but being also expressed at lower level in Bowman’s capsules (WT1 and GLEPP1). However, these markers are not expressed in the tubulointerstitium. To the best of our knowledge, it is difficult to find negative markers for Bowman’s capsules, which could further exclude the contamination of tubular cells and interstitial cells in RNA from Bowman’s capsules.Furthermore, due to the low amount of starting material we were not able to perform a comprehensive reference gene analysis in hemalaun-stained micro-dissected Bowman’s capsule transections. Therefore, we have chosen the geometric mean of PGK1 and GAPDH as normalization factor for PEC, tubulointerstitium and glomeruli on the basis of the current literature , 24.q values using our suggested reference transcripts (PGK1 and PPIA) can compensate for different amounts of RNA purity and quantity [200 value and fluorometric analysis) or the sample has to be excluded.In summary, we show the feasibility for micro-dissecting glomerular and Bowman’s capsule transections followed by evidence-based recommendations for quantitative mRNA analysis. We recommend micro-dissecting at least 60 unstained glomerular or 300 hemalaun-stained Bowman’s capsule transections from FFPE renal biopsies to obtain reliable results equivalent to larger amounts of tissue. We provide evidence that RNA quantity is within an acceptable range even for low RNA purity. Therefore, we suggest the following pragmatic approach: in case of 60 available unstained glomerular transections, quantity and purity control is optional for documentation but not gainful regarding further analytical steps, because (I) the range of RNA concentrations in equal amounts of micro-dissected glomerular transections is low and (II) appropriate normalization of Cquantity . HoweverAdditional file 1. Additional tables.


We evaluated the diagnostic and clinical usefulness of blood specimens to detect Middle East respiratory syndrome coronavirus infection in 21 patients from the 2015 outbreak in South Korea. Viral RNA was detected in blood from 33% of patients at initial diagnosis, and the detection preceded a worse clinical course. Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic, betacoronavirus lineage C RNA virus that was first identified in Saudi Arabia in 2012  of serially diluted 105 copies/μL of upE RNA .Specimens were stored at −80°C before analyses. Viral RNA was extracted and eluted with a MagNA Pure LC 2.0 automated nucleic acid extractor and MagNA Pure LC total nucleic acid isolation kit  according to the manufacturer’s instructions. Specimen volumes were 100 μL EDTA whole blood and 200 μL serum, and elution volumes were 100 μL for EDTA whole blood and 50 μL for serum. One-step, real-time reverse transcription PCR (rRT-PCR) was performed for the 3 MERS-CoV gene regions  with an AgPath-ID One-step RT-PCR kit  and an ABI7500 real-time PCR system (Applied Biosystems). Human ribonuclease (RNase) P was amplified in parallel for sample quality control  Table 1.The results of the blood viral RNA analyses did not affect clinical management. We assessed the relationships among clinical and molecular diagnostic factors with the IBM SPSS Statistics program 22.0 . In each test, p<0.05 was considered statistically significant. The institutional review board of the National Medical Center approved this study (H-1508-057-002).t of 37.55, and 1,300 copies/mL serum .We assessed patient demographics, their clinical features, and disease outcomes  Table 2.>37.5°C on the sampling date (p = 0.007), requirement for mechanical ventilation during the following clinical course (p = 0.003) and extracorporeal membrane oxygenation (p = 0.025), and patient death . Blood viral RNA positivity was not associated with viral Ct in the initial diagnostic lower respiratory specimens, or requirement of oxygen supplementation during the following clinical course. Between the blood viral RNA-positive and -negative groups, we found no differences in age, duration from symptom onset to diagnosis of MERS-CoV infection, or an invasive procedure before the specimens were obtained  real-time reverse transcription PCR; viral RNA analyses of MERS-CoV–infected patients; and statistical relationships among clinical and molecular diagnostic factors.


However, the mechanism by which this NLS/CPP region mediates interaction with the nuclear import receptors remains to be resolved structurally. Here, we establish that the HIV-1 Tat:NLS/CPP is able to form a stable and direct interaction with the classical nuclear import receptor importin-α and using x-ray crystallography, we have determined the molecular interface and binding determinants to a resolution of 2.0 Å. We show for the first time that the interface is the same as host factors such as Ku70 and Ku80, rather than other virus proteins such as Ebola VP24 that bind on the outer surface of importin-α.HIV-1 has caused 35 million deaths globally, and approximately the same number is currently living with HIV-1. The trans-activator of transcription (Tat) protein of HIV-1 plays an important regulatory function in the virus life cycle, responsible for regulating the reverse transcription of the viral genome RNA. Tat is found in the nucleus of infected cells, but can also invade uninfected neighbouring cells. Regions within Tat responsible for these cellular localisations are overlapping and include a nuclear localisation signal (NLS) spanning  HIV-1 encodes three groups of proteins that are common in all retroviruses. The gag polyprotein, pol polyprotein and gp160 precursors are structural proteins that form the outer shell of the virus particle, and are processed to produce proteins for the virion interior. The accessory regulatory proteins, Vif, Vpr, Vpu and Nef, interact with cellular ligands and function as adapter molecules or to inhibit normal host function. The third group are the essential regulatory elements, Tat and Rev. The primary role of Tat is in regulating the reverse transcription of viral genome RNA, whilst Rev is responsible for the synthesis of major viral proteins for viral replication2.The HIV-1 virus has spread worldwide, infecting 60 million people, and causing more than 25 million deaths. More than 30 million people currently live with the disease3, and these functions occur within the nucleus of infected cells. Tat has been shown to localise to the nucleus in many studies, however, the mechanism by which it interacts with the nuclear import receptors has not been elucidated structurally5.Tat is a transcriptional trans-activator and plays an important role during HIV-1 replication by binding to a short-stem loop structure, known as the transactivation response element (TAR) located at the 5′ end of HIV RNAs. It assists in the elongation phase of HIV-1 transcription so that full-length transcripts can be produced7. Upon entry to the nucleus, the heterotrimer transport complex is dissociated by the small GTPase Ran, releasing the NLS-containing cargo, and allowing recycling of the import receptors back to the cytoplasm9.Nuclear import can occur through passive diffusion (<45 kDa) or by energy dependent nuclear import receptors. The classical nuclear import pathway is the best characterised mechanism and is mediated by an adaptor molecule, importin-α, also known as the classical nuclear import receptor, binding cargo that can display a nuclear localisation signal (NLS). The transport carrier importin-β interacts with importin-α, and mediates translocation across the nuclear envelope through interactions with the nucleoporin proteins lining the nuclear pore complex48GRKKRRQRRRAPQN61;CPP) has been shown to effectively carry a large range of cargoes, from nanoparticles, peptides, nucleic acids and even proteins into cells and the nucleus14. In vitro studies have shown that Tat is able to bind nuclear import receptors which mediate nuclear localisation15, however, a structural basis for this interaction remains to be elucidated. There has also been some debate in the literature about whether Tat can bind directly to importin-α16 or importin-β15. To determine the precise binding determinants that mediate interaction between the nuclear import receptor and Tat, the entire cell penetrating region of HIV-1 Tat, 48GRKKRRQRRRAPQN61, was recombinantly expressed as a GST-fusion and tested for binding to both importin-α and importin-β16. We found a strong and direct interaction between Tat:NLS/CPP and importin-α, and no direct interaction with importin-β. Together with structural elucidation of the interface by x-ray crystallography, this study provides new insights into the interface between these two proteins which mediate localisation of Tat to the nucleus.The HIV-1 Tat derived cell penetrating peptide (48GRKKRRQRRRAPQN61) were codon optimised for expression in E. coli and cloned into the PGEX4T-1 vector at BamHI/EcoRI sites with an additionally engineered N-terminal TEV site for GST-tag cleavage. An isolate of mouse importin-α  that lacks the auto-inhibitory N-terminal importin-β binding (IBB) domain (residues 70–529) and cloned into the pET30 expression vector has been described previously17. An isolate of mouse importin-β  was cloned into the pMCSG21 vector using protocols described previously19.Tat residues , and lysed by two freeze-thaw cycles. The soluble cell extract was injected onto a five mL HisTrap HP column  and washed with twenty column volumes of His buffer A on an AKTApurifier FPLC. The sample was eluted using an increasing concentration gradient of imidazole, and eluent fractions were pooled and loaded onto a HiLoad 26/60 Superdex 200 column, pre-equilibrated in buffer A . Fractions corresponding to the correct molecular weight were collected, and assessed for purity by SDS-PAGE.Overexpression of importin-α and importin-β was performed using the autoinduction method according to Studier600 of 0.6. Following growth for 24 h, cells were harvested by centrifugation, at 6,000 rpm for 30 min and the cell pellet resuspended in buffer A and stored at −20 °C. The soluble cell extract containing the GST:Tat-NLS fusion was injected onto a GST 5 mL HP column pre-equilibrated in GST buffer A and washed with GST buffer A until the UV reading stabilised to baseline. The purified importin-α or importin-β was then added to the GST column, washed for a further ten column volumes, and eluted in GST buffer A containing 10 mM glutathione. To cleave the GST affinity tag from the Tat:NLS/CPP importin-α, TEV protease cleavage was undertaken overnight, and continued until cleavage was complete. The protein mixture was further purification by size-exclusion chromatography on a HiLoad 26/60 Superdex 200 column , and the complex concentrated to 7 mg/mL using an Amicon MWCO 10 kDa filter, aliquoted, and stored at −80 °C.Tat-NLS was over-expressed as a GST-fusion protein using IPTG to induce the cells at an ODThe final crystallisation condition contained 1.25 M sodium citrate pH 7 and 10 mM DTT. The Tat:NLS/CPP importin-α complex was screened using hanging drop vapour diffusion method where the protein was mixed in a 1:1 ratio with crystallization condition containing reservoir solution and incubated at 296 K. Large rod shaped crystals grew after four days, and the crystals were cryoprotected in a reservoir solution 20% glycerol prior to being flash cooled to 100 K in liquid nitrogen.22 and scaled and merged using Aimless24. The data was phased by molecular replacement using Phaser25 and Protein Data Bank (PDB) structure 5FC8 as a search model. Model rebuilding and refinement were undertaken in Coot28 and Phenix29, respectively.A single crystal was used to collect x-ray diffraction data on the MX2 crystallography beamline at the Australian Synchrotron. The diffraction data was processed using iMosflmD, glutathione agarose beads washed in GST buffer A were saturated with purified GST-Tat:NLS/CPP. Beads were washed three times in GST buffer A and distributed equally in 10 µL aliquots. To each aliquot, 100 µL of two-fold serially diluted importin-α was added, with the initial concentration of 30 µM. One additional tube containing 0 µM importin-α was used as a control. The samples were incubated for one hour at 4 °C before being washed twice with 1 mL of GST buffer A. Binding was assessed by adding 20 µL of tris-glycine sample loading buffer to the beads, boiled for 10 min, and analysed by SDS-PAGE. Images were recorded using BioRad Gel Doc system and processed in ImageJ30. The data was normalised across each replicate experiment and data analysed using one-site specific binding analysis performed in Prism version 7.0b for Mac, GraphPad Software, La Jolla California USA, www.graphpad.com.For determination of the dissociation constant, KThe NLS/CPP region of Tat, spanning residues 49–61, have been shown to contain a functional NLS, however, there has been recent debate as to whether the highly basic cell penetrating peptide region is bound using the importin-α adapter, or can bind directly to importin-β. Since this region contains a large stretch of positively charged residues, many of which of which could fit the definition of a classical NLS binding to importin-α, or an Arg rich importin-β interaction, we tested binding against both types of receptors. Here, we immobilised the GST-Tat:NLS/CPP fusion protein onto a glutathione column, washed the column, then passed each respective importin over the immobilised proteins to assess binding. We observed that most of the importin-α was retained on the column Fig. , whilst To determine the structural basis for the interaction between the nuclear import receptor importin-α and Tat NLS/CPP, both proteins were purified to homogeneity and isolated as an equimolar complex using the following series of purifications. The nuclear import receptor importin-α was first purified by 6-His affinity and size exclusion chromatography, then loaded on a column containing purified GST-Tat:NLS/CPP. The excess importin-α was removed by washing the column extensively and following elution, the GST affinity tag was removed by proteolytic cleavage with the TEV protease. The mixture was then purified by size exclusion chromatography, where the importin-α:Tat NLS/CPP complex (>58 kDa) was successfully separated from excess Tat NLS/CPP (<5 kDa), resulting in a homogenous equimolar complex for crystallisation.° of data, collected at 0.5° oscillations, were indexed, merged and scaled using iMosflm v.1.0.722 and AIMLESS24  motifs as described previously2–4 Fig. . There a2–4 Fig. . Tat resion Figs  and 4. F32.To estimate the binding affinity, importin-α was serially titrated against equal concentrations of HIV-1 Tat:NLS/CPP, and binding captured using a GST-pulldown. The binding affinity was determined to be 1.2 ± 0.2 µM from three replicates Fig. . The bin15, whereas another study has shown that it is dependent on importin-β16. Here, we show that the C-terminal 55RRR is not providing additional binding to importin-α, and of the residues visible in the crystal structure 48GRKKRRQR, only residues 48GRKKRR mediate binding with importin-α. Our results support the findings of Ruben et al., who have shown nuclear import can be mediated by Tat-NLS/CPP residues GRKKR16. This binding motif is consistent with the previously defined monopartite class 2 NLSs33. The P1-P5 binding determinants in Tat:NLS/CPP are resolved within the presented 2.0 Å structure, and are consistent with previously solved structures (Table There has been contention as to which nuclear import receptor is responsible for the nuclear translocation of Tat. One study suggests Tat is importin-α mediatedes Table .Table 3P32 (Table 49RKKRR fit within the requirements of the P1-P5 NLSs and bind importin-α in a similar fashion to other importin-α bound NLS structures, whilst other positively charged residues 55RRR were found not to bind in our structure. The similarities between HIV-1 Tat:NLS/CPP and previously reported NLS importin-α structures can be seen in sequence conservation (Table The major binding site of importin-α interact with five principal binding determinants in NLSs, known as P1-P5 Table . These b32 Table  residueson Table  and fromSupplementary Information


Symbiosis is a phenomenon that allows organisms to colonise a wide range of environments and occupy a variety of ecological niches in marine environments. Large benthic foraminifera (LBF) are crucial marine calcifiers that rely on photo-endosymbionts for growth and calcification, yet the influence of environmental conditions in shaping their interactions with prokaryotic and eukaryotic associates is poorly known.Amphistegina lobifera across a physio-chemical gradient on the Great Barrier Reef (GBR). We collected samples from three reef sites located in the inner-, mid- and outer-shelf regions of the northern section of the GBR. Results showed the consistent presence of Bacillaryophyta as the main eukaryotic taxa associated with A. lobifera across all reef sites analysed; however, the abundance and the diversity of prokaryotic organisms varied among reef sites. Inner-shelf specimens showed the highest diversity of prokaryote associates, with a total of 231 genotypes in their core microbiome. A total of 30 taxa were identified in the core microbiome across all reef sites. Within these taxa, Proteobacteria was the most abundant bacteria present. The presence of groups such as Actinobacteria was significantly correlated with inner-shelf populations, whereas the abundance of Bacteroidetes and Firmicutes was associated with A. lobifera collected from mid- and outer-shelf reef sites.Here, we used next-generation sequencing to identify eukaryotic photosynthesizing and prokaryotic microbes associated with the common LBF We found that benthic foraminifera form stable and persistent symbiosis with eukaryotic partners, but flexible and site-specific associations with prokaryotic microbes that likely influence the ecological success of these crucial calcifying organisms on the GBR.The online version of this article (doi:10.1186/s40168-017-0257-7) contains supplementary material, which is available to authorized users. Symbiotic associations expand both the diversity of potential ecological niches, and the metabolic capabilities of the host-symbiont partnerships . Bacteri3) test and harbour algae as photo-symbionts [2 g CaCO3 m−2 y−1. Diverse groups of modern LBF host a wide variety of endosymbiotic algal groups  and cyanobacteria, so foraminifera are particularly favourable partners for the establishment of symbioses [Reef-dwelling large benthic foraminifera (LBF) are single-celled protists that build a calcium carbonate , which was consistently distributed across reef sites. Comparison of this OTU sequence using the Nucleotide BLAST of the National Centre for Biotechnology (NCBI) database showed 97% similarity to the diatom belonging to the order Fragilariales. Inner-, mid- and outer-shelf specimens of A. lobifera showed an average abundance of 96.06 ± 0.76%, 70.23 ± 5.89% and 81.71 ± 2.38% (mean ± SEM), respectively  = 2.65, p = 0.02; Fig. A. lobifera differ from those found in the mid- and outer-shelf  = 11.95, p = 0.0001; Additional file The analysis of 18S rRNA of photosynthetic taxa sequences showed that specimens of A. lobifera specimens collected from the mid- and outer-shelf. Cores from the mid- and outer-shelf consisted of more diatom OTUs than those from the inner-shelf. Ten OTUs were ubiquitous , a total of 451 OTUs remained, belonging mainly to the following bacterial taxa across all reef sites: Proteobacteria , Planctomycetes (10.04 ± 0.46%), and Firmicutes  = 2.23, p = 0.0002; Fig. A. lobifera collected from the inner-shelf and both mid- and outer-shelf sites was due to the presence of a different lower raking taxa within Firmicutes, Actinobacteria and Bacteroidetes, whereas the dissimilarity between mid- and outer-shelf sites was mainly due to the presence of different Firmicutes and γ-Proteobacteria taxa , Actinobacteria (4), Firmicutes (4), Planctomycetes (3) and γ-Proteobacteria (1). However, Firmicutes showed the highest average abundance in the core across all reef sites , whereas the lowest diversity of bacterial taxa was found in inner- and outer-shelf samples. It is noteworthy that Chloroflexi, which was exclusively found within the inner-shelf, was present in all inner-shelf samples. Specimens collected from the mid-shelf showed a high average proportion of Bacteroidetes, while outer-shelf samples showed a high average proportion of Planctomycetes.Analysis of the core microbiome showed that ied Fig. , 13 weretes Fig. . Core miA. lobifera within each population drove differences in the community structure of bacteria at different reef locations. In contrast, the photo-symbiotic profile in A. lobifera, mainly the taxanomic composition of the rare diatoms, was site-specific. Thus, the most abundant photo-symbiont taxa in A. lobifera were highly conserved among reef sites, but bacterial communities were very flexible. Differences in environmental conditions, mainly between inner-shelf and mid/outer-shelf locations, are likely to have a major influence in shaping the bacterial communities associated with A. lobifera populations. On the GBR, factors such as nutrient concentration and temperature vary across an inshore-offshore gradient. Inshore reef sites are more prone to temperature fluctuations and influx of dissolved inorganic nutrients from terrestrial runoff, whereas offshore sites display more stable temperature conditions and low nutrient concentrations [The dominant photo-symbiotic partners in large benthic foraminifera (LBF) are well known and described ; howevertrations , 37. TheNanofrustulum shiloi is known to be a common endosymbiont species in A. lobifera [A. lobifera, suggesting that A. lobifera associates with this species regardless of continental shelf location. Other diatom species were also identified, within the orders Naviculales and Bacillariales, although at lower densities , Planctomycetes, Bacteroidetes and Firmicutes were consistently the most abundant and diverse phyla of bacteria associated with A. lobifera. However, the classes and genera within these major phyla varied significantly across sites, indicating flexibility in prokaryotic association within A. lobifera from different habitats. Bacterial diversity in A. lobifera collected from the inner-shelf was the highest. It is not possible to determine the kind of interaction bacterial taxa have with A. lobifera; however, the consistent within and between site patterns observed in the bacterial associations indicate that bacterial communities are non-random. Uthicke and McGuire [A. lobifera. However, bacterial communities previously detected in sediment samples along a cross-shelf gradient [A. lobifera.The high bacterial diversity among foraminifera species found in laboratory studies has been found to be a result of their close association with reef rubble, sediment and filamentous algae . In the  McGuire  argued t McGuire , which b McGuire . The mecgradient  differ fActinobacteria, which is commonly associated with freshwater runoff [A. lobifera collected from the inner-shelf reef site. Actinobacteria is also known to be a common invertebrate symbiont, commonly associated with zooxanthallae corals and can be associated with marine sediments [Cyanobacteria associated with A. lobifera collected from mid/outer-shelf reef sites might be explained by higher light availability for this photo-autotrophic group of bacteria, which has a competitive advantage in oligotrophic environments [Cyanobacteria also naturally occur as benign endosymbionts in some LBF species [A. lobifera to colonise a wide range of environmental conditions.Phyla such as r runoff , 43, shoediments , 44. Thiediments , which cronments . Cyanoba species  and playA. lobifera from the inner-shelf showed the lowest diversity of diatoms, and the highest diversity and abundance of prokaryotic symbionts. No diatom was exclusively found in A. lobifera from the inner-shelf. While the number of prokaryotic microbes shared between different A. lobifera populations was small, the core diatom biome was large, with the vast majority of diatoms conserved in all replicate individuals per site. In contrast, the core microbiome within each site, especially in inner- and mid-shelf specimens, was higher than the core shared by all three sites together. These results indicate that prokaryote microbes are likely to play a crucial role in the ecology of A. lobifera. Environmental variables such as water quality, temperature fluctuations and light exposure may help drive the compositional differences in the prokaryotic and eukaryotic microbial communities in A. lobifera from the GBR A. lobifera specimens collected from different habitats display substantially different responses when exposed to experimental conditions such as increased temperature and nitrate [In summary,  nitrate , as theyA. lobifera specimens are able to establish strong but not specific symbiosis with their eukaryotic endosymbionts. This species also showed a diverse and flexible interaction with bacterial associates, which varied among reef sites. This study, combined with previous work [We demonstrated that ous work , 48, demous work , understA. lobifera attached was collected from inner-, mid- and outer-shelf reefs located on the northern GBR in August 2014  under a stereoscope to remove any particles from the test exterior and photographed. Specimens were then snap frozen in liquid N2 and kept at −80 °C until analysis.Dead coral rubble with 014 Fig. . SamplesIn the laboratory, specimens were taken from −80 °C, rinsed in cold sterile phosphate buffer saline 3× and immediately placed individually in 1.5-ml tubes for DNA extraction. Each tube contained 200 μl of lysis buffer  containing Proteinase K and crushed using a micro homogenizer. Samples were incubated overnight at 56 °C and then were purified using a silica-membrane-based nucleic acid technique . Extracted DNA concentration was quantified using a Qubit® High-sensitivity dsDNA assay kit . Purified total DNA samples were sent to Molecular Research Laboratory  for the PCR amplification and Illumina sequencing of the rRNAs of eukaryotic and prokaryotic associates.Bacterial 16S and eukaryotic 18S rRNA samples were PCR-amplified from the genomic DNA template and were sequenced using the Illumina HiSeq250 platform. PCR amplification was performed using the universal Eubacterial primers 27 F (5′ -AGAGTTTGATCCTGGCTCAG) and 519R (5′ GTNTTACNGCGGCKGCTG), which target highly variable regions V1, V2 and V3 of the 16S rRNA. We also targeted eukaryotic 18S rRNA using the following primer set: Euk1391 (5′ GTACACACCGCCCGTC) and EukBRev (5′ TGATCCTTCTGCAGGTTCACCTAC). A single-step 30-cycle PCR using HotStarTaq® Plus Master Mix Kit  was used under the following conditions: 94 °C for 3 min, followed by 28 cycles of 94 °C for 30 s; 53 °C for 40 s and 72 °C for 1 min; after which a final elongation step at 72 °C for 5 min was performed. Following PCR, all amplicon products from different samples were mixed in equal concentrations and were purified using Agencourt Ampure beads . Samples were sequenced utilising Illumina HiSeq250 instruments and reagents . Negative controls for each amplification and sequencing stage were utilised. The sequence data were processed using the software package QIIME . 18S rRNA. lobifera populations collected from differing reef sites were analysed using the software QIIME and PRIMER 6.1.15 with PERMANOVA+ 1.0.5 [A. lobifera is known to harbour diatoms, we filtered out the other algal groups from the 18S dataset and retained the OTUs classified as ‘Bacillariophyta’ in order to compare the composition of endosymbionts among reef sites using PERMANOVA. For both 16S and 18S datasets, a SIMPER analysis was performed on the fourth root transformed datasets to determine those microbial or eukaryotic groups that were responsible for the significant dissimilarity between A. lobifera specimens collected from different locations, as identified using pairwise comparisons [A. lobifera specimens collected from different reef sites, core microbiome and diatom biome were identified using the software package QIIME. Core microbiome and diatom biome were defined as the OTUs that were present in 100% of the samples across the reef sites. Venn diagrams were generated utilising the core diatom species composition and microbiome and constructed with the online Venn diagram software from Bioinformatics and Evolutionary Genomics (http://bioinformatics.psb.ugent.be/software/details/Venn-Diagrams).Differences in eukaryotic and prokaryotic microbes associated with A+ 1.0.5 . Prior tA+ 1.0.5 . DiffereA+ 1.0.5  pipelineparisons . SIMPER parisons . For theparisons , 59. Theparisons . Total rAdditional file 1: Table S1.A. lobifera collected from different reef sites. (XLS 75 kb)Absolute and relative abundance of photosynthetic eukaryotes associted with Additional file 2: Table S2.Amphistegina lobifera collected from different reef sites. Table S4. Results of main effects PERMANOVA model and pairwise comparison of Bacillariophyta taxonomic composition in Amphistegina lobifera collected from different reef sites. Table S6. Results of main effects PERMANOVA model and pairwise comparison of bacterial community in Amphistegina lobifera collected from different reef sites. Table S7. Results of alpha diversity comparison between samples using a parametric t test using a t distribution. (DOC 58 kb)Results of main effects PERMANOVA model of photosynthesizing eukaryotic taxa associated with Additional file 3: Table S3.A. lobifera across all reef sites. (XLS 39 kb)Relative abundance of Bacillariophyta associated with Additional file 4: Table S5.A. lobifera across all reef sites. (XLS 213 kb)Absolute and relative abundances of OTUs identified, and main bacterial taxa associated with Additional file 5: Figure S1.A. lobifera across all three reef sites. (TIFF 480 kb)Species richeness estimator (Chao 1) of bacterial taxa associated with


Pervious randomized studies have demonstrated survival benefit in favor of tyrosine kinase inhibitors (TKIs) compared to cytokines in metastatic clear cell renal cell carcinoma (RCC). However, the role of TKIs for treating brain metastasis from RCC remains unknown. Previous studies have reported possible activity of sunitinib and sorafenib in RCC patients with brain metastasis. We report on patient with metastatic RCC who responded to first-line sunitinib but then progressed with multiple brain metastasis, but with controlled extra-cranial metastatic disease. The patient was treated with whole-brain palliative radiotherapy followed by treatment schedule of pazopanib at standard dose of 800 mg/day which was associated with a response in brain metastasis. Subsequently, she was re-challenged at reduced dose of 600 mg/day and developed further response in metastatic brain lesions. She lived for more than 3 years from initial diagnosis of brain metastasis. This is the first case report of sequential TKI therapy for treating metastatic RCC with brain metastasis and supports the probable use of pazopanib as potent TKI for treating patients with cerebral metastasis. The development of brain metastases has been reported in 10-25% of patients with renal cell carcinoma (RCC) with an average interval of approximately 17 months from original diagnosis and development of extra-cranial metastasis . In contWe report on a case with metastatic RCC who developed response to first-line TKI therapy with sunitinib, but then progressed with development of multiple brain metastases. The patient was treated with WBRT and re-challenged with further TKI (pazopanib) that induced a partial response and regression of brain metastasis. The patient had unusually prolonged survival of 3 years from diagnosis of brain metastasis.A 73-year-old Caucasian female presented in January 2009 with a large 9 × 8 cm tumor involving the left kidney. She underwent a left radical nephrectomy and post-operative histology showed presence of typical clear cell carcinoma of kidney (Fuhrman grade 3) with involvement of renal vein with pathological staging of T3aN0 (TNM version-7) completely excised RCC. She did not receive any adjuvant therapy. She relapsed in February 2010 when a routine surveillance CT scan demonstrated metastatic lesion in the upper lobe of right lung with associated mediastinal and hilar lymphadenopathy. She was asymptomatic with WHO performance status of one and the hematological and biochemical profile was normal. She was classified as favorable risk based on the Memorian Sloan Kettering Cancer Center prognostic stratification model. She commenced TKI therapy sunitinib at dose of 50 mg/day based on 4 weeks “on” and 2 weeks “off” schedule. She underwent staging CT scan in September 2010 that demonstrated complete response in hilar lymphadenopathy and more than 50% reduction in size of lung metastasis . She conIn June 2011 a follow-up CT showed small volume lung metastasis and stable appearances of brain metastasis. There was an improvement in her clinical condition and performance status (WHO grade 1-2), but she had commenced therapeutic anticoagulation with low-molecular weight heparin in view of below-knee deep vein thrombosis and pulmonary embolism. In view of reappearance of lung metastasis, she was commenced on pazopanib 800 mg/day that she tolerated well with no significant toxicities. She underwent repeat imaging 3 months later that showed an improvement in lung metastasis and also response in the brain metastasis . She conThe management of RCC was revolutionized following the results from a pivotal phase III study published in 2007 demonstrating the effectiveness of TKI therapy with sunitinib improving survival outcomes compared to cytokines . More reBoth sunitinib and pazopanib are small molecular TKIs with similar mechanisms of action and induce blockade of vascular endothelial growth factor (VEGF) types 1 through 3, platelet-derived growth factor (PDGF-α and PDGF-β), KIT, Fms-like tyrosine kinase-3 (FLT3), and colony-stimulating factor-1 pathways. There are pre-clinical data from animal studies that both sunitinib and pazopanib cross the blood-brain barrier (BBB) . In miceThere is limited evidence on the role of TKIs in the treatment of metastatic RCC with brain metastasis. All the pivotal phase III studies have excluded patients with brain metastasis. However, TKIs may have activity in treatment of brain metastasis as indicated by several case reports of response after exposure to sunitinib . In an eThis case report is unique as the patient progressed on initial TKI therapy with sunitinib, but responded to further sequential TKI inhibition with pazopanib. There is some evidence on possibility of objective responses with sequential VEGF TKI inhibition , but thiThe clinical history of our case and the response in brain metastasis observed with pazopanib raises some extremely important and pertinent questions. Does the development of brain metastasis on TKI therapy in the presence of response in extra-cranial sites of metastatic disease be truly characterized as TKI failure, and what is the best therapeutic approach for these patients? It is more than likely that the development of brain metastasis in this situation represents inability of drug to cross the BBB, rather than representing loss of drug activity. Therefore, appropriate treatment of brain metastasis followed by re-challenge schedule of TKI appears to be a reasonable therapeutic paradigm to follow in these circumstances.In our patient MRI showed multiple small brain metastasis and therefore patient received WBRT compared to surgery or SRS therapy. We decided to treat the patient with pazopanib given the favorable tolerance profile of the drug as the patient had experienced significant fatigue following completion of radiotherapy. It remains unknown whether the response to pazopanib may have been influenced by WBRT with its complex modulation of blood brain permeability, and whether re-challenging the patient with sunitinib may have induced a similar response. Does the response in brain metastasis induced by pazopanib in a patient progressing on sunitinib imply that pazopanib may be a more effective agent for treating brain metastasis? In contrast to sunitinib and sorafenib, there is no definite evidence on the possible activity of pazopanib in metastatic RCC with brain metastasis. We searched the literature and could identify only one report on pazopanib-induced response in brain metastasis in metastatic renal cancer. The report described a patient with papillary variant of RCC with multiple brain metastasis who was treated with WBRT followed by multiple lines of systemic therapy. Patient was treated with sunitinib, everolimus, standard-dose pazopanib (800 mg/day), sorafenib, and high-dose pazopanib (1 g/day). Patient was developing progressive brain lesions on standard-dose pazopanib which responded when the dose was escalated to 1 g/day. The patient had survival of 23 months from diagnosis of brain metastasis. The authors hypothesized that there may be a dose-response relationship with probable superior penetration of BBB with the increased dosage of pazopanib that reinforces the principles and importance of drug titration with targeted therapy . In contIn summary, this is the first case report of activity of pazopanib in brain metastasis arising from conventional renal clear-cell carcinoma. This report demonstrates robust and sustained activity of pazopanib for treating brain metastasis in metastatic RCC arising on background of progression on first-line sunitinib. This report highlights that sequential TKI inhibition may be an appropriate therapeutic strategy to adopt in patient with brain metastasis. There should be further research in the role of pazopanib for treating brain metastasis in metastatic renal cancer.


Wolbachia endobacterial mRNA transcripts from total RNA prepared from the parasitic filarial nematode, Brugia malayi. The obligate Wolbachia endosymbiont is a proven drug target for many human filarial infections, yet the precise nature of its symbiosis with the nematode host is poorly understood. Insightful analysis of the expression levels of Wolbachia genes predicted to underpin the mutualistic association and of known drug target genes at different life cycle stages or in response to drug treatments is typically challenged by low transcriptomic coverage. Cappable-seq resulted in up to ~ 5-fold increase in the number of reads mapping to Wolbachia. On average, coverage of Wolbachia transcripts from B. malayi microfilariae was enriched ~40-fold by Cappable-seq. Additionally, this method has an additional benefit of selectively removing abundant prokaryotic ribosomal RNAs.The deeper microbial transcriptome sequencing afforded by Cappable-seq facilitates more detailed characterization of gene expression levels of pathogens and symbionts present in animal tissues.Efficient transcriptomic sequencing of microbial mRNA derived from host-microbe associations is often compromised by the much lower relative abundance of microbial RNA in the mixed total RNA sample. One solution to this problem is to perform extensive sequencing until an acceptable level of transcriptome coverage is obtained. More cost-effective methods include use of prokaryotic and/or eukaryotic rRNA depletion strategies, sometimes in conjunction with depletion of polyadenylated eukaryotic mRNA. Here, we report use of Cappable-seq™ to specifically enrich, in a single step,  Wuchereria bancrofti, Brugia malayi, B. timori and Onchocerca volvulus) responsible for debilitating human diseases contain Wolbachia, an obligate intracellular endosymbiotic bacterium. In filarial nematodes, Wolbachia are found in the lateral cords of all adult worms as well as within the oocytes and developing embryos in the female reproductive tract [Wolbachia leading to decreased fertility and eventually death of adult worms [Many filarial nematode species , the obligate association is thought to derive from metabolite provisioning between the nematode and bacterium [Wolbachia and its nematode hosts. However, studying the endosymbiont transcriptome has proven challenging as Wolbachia transcripts are relatively few among many nematode transcripts; similar to looking for a needle in a haystack. Next Generation sequencing has provided an unprecedented depth of sequence information that has allowed transcriptomic studies of Wolbachia through the sequencing of mixed total RNA (nematode + Wolbachia) [Wolbachia-host interactions, the Wolbachia coverage remains low. This problem is not restricted to Wolbachia endosymbionts of arthropods and nematodes, but to any microbial symbiont or pathogen resident in a eukaryotic host. For mixed total RNA pools, where the relative proportion of bacterial transcript is low, strategies that allow depletion of eukaryotic rRNA with or without additional steps to deplete prokaryotic rRNA and/or eukaryotic mRNA have been developed [Wolbachia mRNA transcripts from B. malayi total RNA preparations in a single step. Cappable-seq enzymatically caps 5′ triphosphorylated RNA with biotinylated GTP using the vaccinia capping enzyme [7G) cap at the 5′-end and thus cannot be reacted with the vaccinia capping enzyme. Our use of Cappable-seq takes advantage of the fact that prokaryotic mRNA transcripts, such as those from Wolbachia, do not contain an m7G cap, but rather a 5′ triphosphate. This enables Wolbachia transcripts in a mixed pool of nematode/Wolbachia transcripts, to be selectively capped with a biotinylated GTP analog (3´ desthiobiotin-GTP), enriched on streptavidin beads and sequenced to a deeper depth than would be achievable by sequencing total nematode RNA.The precise nature of the essentiality of the acterium . Recentllbachia) –11. Whileveloped ,13. Theseveloped , which ig enzyme . Most euB. malayi and microfilariae (MF) were obtained from the peritoneal cavity of one infected jird .The 3’ desthiobiotin-GTP was synthesized as previously described . Adult mB. malayi adult males and MF were homogenized separately with ceramic beads in CK14 tubes using a Minilys homogenizer (Precellys) and total RNA was extracted by organic extraction using Trizol . Samples were treated with DNase I  before further Trizol extraction and final purification. RNA integrity, purity and concentration were assessed using a Bioanalyzer 2100 (Agilent Technologies).B. malayi MF (25 μg) or adult males (1.5 μg) was capped with 3´ desthiobiotin-GTP using the Vaccinia Capping System (New England Biolabs). Total RNA was incubated with 0.5 mM 3´ desthiobiotin-GTP, 0.1 mM S-adenosylmethionine (SAM) and 70 units of the Vaccinia Capping Enzyme in 1X Capping Buffer for 30 min at 37°C. RNA was then purified using the MEGAClear™ Transcription Cleanup Kit (ThermoFisher Scientific). Two additional washes  with the Wash Solution were performed on column to ensure complete removal of any excess 3´ desthiobiotin-GTP. To maximize recovery, RNA was eluted in 50 μL H2O.Total RNA from 2O and stored at −80°C until further use (‘Capped RNA’ sample).50 μL of eluted RNA was mixed with 50 μL of 10 mM Tris-HCl, pH 7.5, 500 mM NaCl, 1 mM EDTA (wash Buffer A). This mix was added to 100 μL of hydrophilic streptavidin magnetic beads (New England Biolabs) previously washed twice with wash Buffer B  and twice with wash Buffer A (100 μL/wash). The RNA-bead mixture was incubated for 20 min at room temperature with occasional resuspension. Using a magnetic rack, the RNA-bead mixture was washed two times with wash Buffer A, followed by two washes with wash Buffer B (100 μL/wash). All washes (containing unlabeled RNA) were collected, cleaned up using the RNeasy Kit (Qiagen) and stored at −80°C until further use (‘Uncapped RNA’ sample). Beads (containing 3´ desthiobiotin capped RNA) were resuspended in wash Buffer B containing 1 mM biotin and incubated for 20 min at room temperature with occasional mixing. After placing the tube in the magnetic rack again, the supernatant (100 μL), containing the 3´ desthiobiotin capped transcripts was collected and cleaned up using the RNA Clean and Concentrator Kit™ (Zymo), and the RNA eluted in 10 μL HB. malayi MF/adult males, respectively), using the NEBNext® Ultra™ Directional RNA Library Prep Kit for Illumina® (New England Biolabs) according to the manufacturer instructions. Library quality was assessed using a DNA high sensitivity chip on a Bioanalyzer 2100 prior to sequencing. The three libraries  for each sample  were pooled and were sequenced on an Illumina NextSeq (75 bp single-end reads).Prior to library construction, the RNA integrity, purity and concentration of all samples were assessed on an RNA pico or nano chip using a Bioanalyzer (Agilent). Libraries were prepared from capped RNA, uncapped RNA (from bead wash steps above) and total RNA  or to the B. malayi genome (Wormbase version WS236) using the default settings of Bowtie2  [All data was analyzed using a local instance of Galaxy –17. Sequy v 0.2) . Reads ay v 0.2) .B. malayi adult male and microfilarial (MF) transcriptomic libraries. Over 6 million of these reads mapped to the Wolbachia endosymbiont  [B. malayi total RNA mapped to the wBm genome  or 4.8-fold (MF) enrichment in Wolbachia transcripts using Cappable-seq  . Similarm genome . Comparaable-seq . Additioolbachia .Wolbachia transcripts as compared to the total RNA control  to assess whether transcriptomic coverage was enriched with Cappable-seq. Current annotation suggests the wBm genome contains 940 predicted transcripts, including ribosomal RNAs (rRNA) and tRNAs. Total RNA sequencing covered between ~58–69% of the wBm transcriptome with 544/940  and 649/940 (MF) transcripts having FPKM>0  in the B. malayi MF sample and 334 Wolbachia transcripts  in the B. malayi adult sample were detected as expressed using Cappable-seq that were not detected by sequencing total RNA  reveals an average enrichment of ~10 to 40-fold in adult male worms  and MF , respectively  Tables. Wolbachia tRNAs may be enriched by Cappable-seq while others are depleted. Furthermore, a number of pseudogenes were also enriched by Cappable-seq , while these pathways are complete and likely functional within their Wolbachia endosymbiont [Wolbachia for nematode survival, targeting of these essential Wolbachia pathways may have detrimental effects on their parasitic nematode hosts. Unfortunately, transcriptomic analysis of these essential Wolbachia-specific, potentially therapeutic pathways, is often hindered by sequencing total RNA due to low transcript coverage of one or more genes in the pathway. Although gene expression alone does not confirm translation or gene functionality, transcript coverage of nearly every gene in the purine, pyrimidine, heme and riboflavin biosynthesis pathways was enriched using Cappable-seq. Importantly, transcripts for over one third (17/45) of the Wolbachia genes in these pathways were undetectable in B. malayi adult male total RNA, but were detected using Cappable-seq. Godel et al. [D. immitis Wolbachia genes that may be suitable drug targets. Specific targets that have been suggested include proteins involved in nucleic acid synthesis (DnaB), enzymes involved in fatty acid synthesis (FabZ) [Wolbachia target, FtsZ, a cell division protein [Wolbachia-specific drug targets including pyruvate phosphate dikinase (PPDK) [Wolbachia targets in the host-endosymbiont interaction.A number of metabolic relationships potentially responsible for the mutualism between rganisms ,24,25. Fsymbiont . Moreovel et al.  suggestes (FabZ) , and the protein . Of these (PPDK)  and cofae (PPDK)  were alsWolbachia transcripts from microfilarial and adult male B. malayi total RNA. We selected these different life-cycle stages since adult males typically represent a small sample size with a low level of Wolbachia transcription compared to the larger MF samples that have also much higher endosymbiont transcriptional activity [Wolbachia transcripts, corresponding to an average 10 to 40-fold enrichment in Wolbachia transcripts that were detected both before and after Cappable-seq. We also observed significant depletion of Wolbachia rRNA transcripts following Cappable-seq. The levels of enrichment of Wolbachia transcripts from MF and adult males were thus broadly similar despite a nearly 20-fold difference in the amount of total RNA used for Cappable-seq. The levels of Wolbachia transcript enrichment obtained by Cappable-seq surpass those obtained by alternative strategies that use combined rRNA and polyA depletion approaches [Wolbachia endosymbiont transcripts from a large background of host nematode RNA allows deeper sequencing of the Wolbachia transcriptome with reduced sequencing effort and cost. With further optimization of parameters, we anticipate that even greater levels of enrichment might be realized. This method should prove applicable to other mixed RNA transcript samples that contain relatively few uncapped prokaryotic endosymbiont or pathogen RNAs in a pool of multitudinous capped eukaryotic RNAs and allow for more robust differential expression analysis of prokaryotic transcripts.We have used a modified Cappable-seq protocol to enrich activity . Using tproaches . Our useS1 Table(DOCX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.