Resultados de investigación

[Background]: Little is known about whether the overlap syndrome (OS) combining features of chronic obstructive pulmonary disease (COPD) and sleep apnea-hypopnea syndrome increases the risk of stroke associated with COPD itself., [Methods]: We prospectively studied 74 COPD patients and 32 subjects without lung disease. Spirometry and cardiorespiratory polygraphy were used to assess the pulmonary function of the study population and ultrasound measurements of intima media thickness (IMT) as well as the volume of plaques in both carotid arteries were also evaluated., [Results]: Polygraphic criteria of OS were met in 51% of COPD patients. We found that 79% of patients with OS and 50% of COPD patients without OS had atherosclerotic plaques in the left carotid artery (p = 0.0509). Interestingly, the mean volume of atherosclerotic plaques was significantly higher in the left carotid artery of COPD patients with OS (0.07 ± 0.02 ml) than in those without OS (0.04 ± 0.02 ml, p = 0.0305). However, regardless of the presence of OS, no significant differences were observed in both presence and volume of atherosclerotic plaques in the right carotid artery of COPD patients. Adjusted-multivariate linear regression revealed age, current smoking and the apnea/hypopnea index (OR = 4.54, p = 0.012) as independent predictors of left carotid atherosclerotic plaques in COPD patients., [Conclusions]: This study suggests that the presence of OS in COPD patients is associated with larger left carotid atherosclerotic plaques, indicating that OS might be screened in all COPD patients to identify those with higher risk of stroke., Peer reviewed

Additional file 1: Supplementary Figure S1. Expression of RMPs in prostate tumours. A) mRNA expression of RMPs is significantly altered in human normal prostate tissue (N), primary (PT), and metastatic tumour (M). Y-axis shows log2-normalised expression data from Grasso et al. [7],Taylor et al. [6], and Varambally et al. [42] datasets (left panels). Kaplan–Meier curves showing disease-free survival (DFS) of patient groups selected according to decile expression of the indicated RMP genes (middle panel). The right panel shows differential expression in disease-free (DF) and recurrent patient samples from TCGA dataset [3]. B, C) Kaplan–Meier curves representing the disease-free survival (DFS) of patient groups selected according to the decile expression, data from the TCGA dataset [6] (TCGA: n = 491). D, E) PCa cell lines show increased METTL1 protein and mRNA levels. Western blotting showing METTL1, WDR4, AR, PTEN and phosphor-S6K expression (D), and qPCR (E) of normalised mRNA expression (lower panel) in prostate epithelial cell lines (PWR-1E and RWPE-1), benign prostatic hyperplasia cell lines (BPH1), and prostate cancer cell lines (VCap, C4-2, LNCaP, 22Rv1, DU145, and PC3). Mean ± SD (D, E). Statistical tests: ANOVA test (A), log-rank Cox test (A, B); Student’s t-test with Welch’s correction, grouping all data from benign vs. all data from tumour cells ****p < 0.0001 (E)., Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

Additional file 2: Supplementary Figure S2. Regulation of METTL1 expression in PCa. A) Correlation analysis between METTL1 and KLK3 expression, and METTL1 and AR expression in the human primary PCa expression datasets. The plotted values correspond to the log2-normalised expression values. Black line represents linear regression, grey area indicates the limits of the confidence intervals. Pearson's correlation coefficient (R) and p-values are indicated. Grasso n = 88; Taylor n = 183; TCGA n = 497. B) No effect on mRNA expression levels of METTL1 upon dihydrotestosterone (DHT) treatment in LNCaP cells. Mean ± SD, n = 3. C) Graphical representation of PI3K inhibition by different compounds. Small molecule inhibitors used: pan-PI3K inhibitor BKM-120 (BKM), AKT inhibitor MK2206 (MK), mTORC1 inhibitor rapamycin (RAPA), and mTORC1/2 inhibitor Torin (TOR). D, E) METTL1 expression is affected by the inhibition of downstream PI3K pathway members. Western blotting (D) and RT-qPCR (E) analyses of METTL1 expression upon PI3K pathway inhibition in PC3 cells. The cells were treated for 48 h (D) or 8 h (E). Mean ± SD, n = 2 (D) and n = 6 (E). F) Representative images of immune stained sections for Mettl1 and markers for luminal (AR), and basal (K14) cells in Pten-KO prostates (dorsal and ventral lobes) in invasive carcinoma (6 months old mice) and in aged-match wild-type (WT) prostates. Scale bars represent 50 μm. Statistical tests: One-tailed Student’s t-test (B, D, E). *p < 0.05, **p < 0.01, ***p < 0.001., Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

Additional file 3: Supplementary Figure S3. tRNAs are methylated at guanine-7 by METTL1. A) Western blot showing the expression of doxycycline-inducible HA-METTL1 in PC3 cells. B, C) Density distribution of reads per million (RPM) identified after PAR-CLIP analysis of METTL1-bound tRNAs (B) and other RNA species (C) in PC3 (control) and HA-METTL1 expressing PC3 cells. The red line indicates the third lower quartile of total RPMs. D) tRNAs are the most common RNA species that bind Flag-METTL1 in HEK293T cells. Density distribution of reads per million (RPM) identified after PAR-CLIP analysis of METTL1-bound RNAs: The red line indicates the third lower quartile of total RPMs. Data were retrieved from Bao et al. study. E) tRNAs comprise half of the reads of all RNAs bound to METTL1 after PAR-CLIP analysis in HEK293 cells. F) Boxplot representing the median with interquartile range of reads per million (RPM) per transcript bound to METTL1 in HEK293T cells. G) Schematic representation of genomic editing introduced by CRISPR-Cas9 technology in the PC3 METTL1 KO clones used in this study. H) METTL1 mRNA expression levels in METTL1 KO, and WT control clones used in this study. Mean ± SD, n = 3. I) Graphics representing the experimental workflow followed to generate AlkAniline-seq libraries. J) Normalised cleavage signals for METTL1-methylated tRNAs Cys and Ile, and METTL1 non-methylated tRNAs His and Glu in PC3 WT and METTL1 KO cells., Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

Additional file 4: Supplementary Figure S4. Accumulation of 5'tRNA fragments in METTL1 KO cells. A) The most common sequences of 5' terminal guanines (5G) containing 5'TOGs and 4G 5'TOGs are shown. B, C) Northern blot showing the absence of 5'tRNA fragments derived from Lys and Pro tRNA in PC3 WT METTL1 KO cells under normal conditions. D) qPCR showing reduced expression of METTL1 in 22Rv1 cells upon METTL1 silencing using siRNA. Mean ± SD, n = 3. E) Dot blot against m7G showing reduced methylation levels in tRNAs extracted from METTL1-silenced 22Rv1 cells. Mean ± SD, n = 3. F) Northern blot detection of Cys-derived 5'TOGs in METTL1-silenced 22Rv1 cells. Mean ± SD, n = 3. G) Northern blot detection of Cys-derived 5'TOGs in PC3 METTL1 KO cells (second biological replicate), unexposed (0 h) or after 2 and 8 h of oxidative stress exposure. H) Northern blot detection of Lys-derived 5'TOGs in PC3 METTL1 KO cells unexposed (0 h) or after 2 and 8 h of oxidative stress exposure. I) Western blotting of DU145 METTL1 KO and WT cell clones generated using CRISPR-Cas9 technology and parental DU145 (DU) cells. J) Northern blot detection of Cys-derived 5'TOGs in DU145 METTL1 KO cells (second biological replicate), unexposed (0 h) or after 2 and 8 h of oxidative stress exposure. The loading control by red-safe staining (tRNA) is shown in the bottom panels (B, C, F–H, J). Bands corresponding to full-length tRNAs are indicated with stars, and 5’tRNA fragments are indicated with arrows. Statistical tests: One-tailed Student’s t-test (C-F). *p < 0.05., Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

1 file, The current trend of climatic alterations will accelerate the modification of the ocean system by, among other aspects, changing the metal speciation and its bioavailability which may have an impact in their accumulation by marine organisms. Understanding the impact of these potential changes is essential for future risk assessment of metal contamination. In the present study, we selected the species Mediterranean mussel (Mytilus galloprovincialis) as the main European aquaculture production bivalve and due to its widespread use for biomonitoring purposes. A long-term test (2 months) was carried out to explore the impact that global change in the marine environment (warming and CO2 increase) may exert on the accumulation of dissolved trace metals (Cu, Co, Pb, Cd, Cr, As and Ni) in different body parts of mussels (foot and soft tissue). Studied mussels were collected at two different climatic locations (Atlantic and Mediterranean Sea) and exposed to unspiked, unpolluted seawater from the Vigo Ria (NW Iberian Peninsula). Results showed that under the global change conditions proposed in this study (1100 pCO2 and 25 °C), the increase in temperature resulted in a lower condition index and byssus strength for mussels from Atlantic Sea, while Mediterranean sea mussels, adapted to higher temperatures, did not show remarkable variations. According to trace metals accumulation in different body parts of the studied mussels, it was observed that the effect of increasing CO2 alone did not show to have an impact in the bioaccumulation, but the combined stressors (increase in CO2 and temperature) may lead to an increase in the bioaccumulation for some elements. The increase in temperature resulted in a decrease of the Cu content of foot tissue (byssus gland) in mussels from Atlantic Sea, which is in accordance with the lower byssus strength observed under such conditions. Our results indicate that the expected seawater temperature increase, which will be produced gradually during next decades, should be further study to ensure the species adaptability and aquaculture production, Peer reviewed

Additional file 5: Supplementary Figure S5. 5’TOGs bind to translation initiation factors. A) No differences in protein expression of translation initiation complex factors were detected by western blotting in PC3 parental, WT, and METTL1 KO cells. The bottom boxplot shows the normalised protein level quantification, and the dotted lines indicate the mean protein levels in WT cells. B) Global protein synthesis rate measured by OP-puromycin (OP-puro) incorporation in PC3 METTL1 KO cells compared to the control (WT) after NaAsO2 exposure at the indicated time points. Fluorescence was normalised to cell size (FSC). n = 3; mean ± SD. C) Representative western blot showing translation initiation factors pulled down by m7G-cap sepharose beads in PC3 METTL1 KO vs. WT cell extracts. D) Representative western blot showing translation initiation factors pulled with synthetic biotinylated-5'TOG in PC3 WT cells transfected with biotinylated-5'TOGs (5'TOG), anti-TOG (ANT) or scramble RNA (-). E) Representative western blot showing mRNA-cap-bound translation initiation factors after 5'TOG (TOG), anti-TOG (ANT), or scramble control (Ctrl) transfection in PC3 WT and METTL1 KO cells. Quantification of western blots are shown in Fig. 5 (C, D, E). Statistical tests: One-tailed Student’s t-test (A), and multiple t-test (B); ***p < 0.001,, Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 6: Supplementary Figure S6. METTL1 mediated methylation promotes cell proliferation, and tumour growth in vivo. A) Proliferation of DU145 METTL1 KO and WT cell clones. Mean ± SD, n = 6. The thick dotted line represents the average growth of the WT and KO cells. B) Proliferation of METTL1-silenced 22Rv1 cells. Mean ± SD, n = 3. C) Cell cycle analysis of PC3 METTL1 KO, WT, and parental cells showing decreased cell cycle progression in METTL1 KO cells. Mean ± SD, n = 3. The dotted lines indicate the mean of three biological replicates. D) Representative images of BrdU staining of three clones of PC3 METTL1 KO and WT cells. Quantification is shown in Fig. 5. E) Schematic representation of generation of single-cell-derived spheroids, and representative images of single-cell-derived spheroids (lower panel). Quantification is shown in Fig. 5. F) METTL1 depletion affects tumour growth in vivo. Immunohistochemical staining for METTL1, Ki67, and cleaved caspase 3 (Cl-Casp3) in PC3 METTL1 KO and WT cell-derived xenografts. Right charts show the quantification of Ki67 + and Cl-Casp3 + cells per microscopic field. Mean ± SD, n = 5, and ten images per biological replicate. G-I) Protein expression (G) and m7G methylation levels (H, I) of a second PC3 METTL1 KO cell clone (KO2) ectopically expressing an HA-tagged wild-type (WT) or catalytic dead mutant (AFPA) version of METTL1. METTL1 KO2 cells were infected with the empty vector (eV) as a control. Methylene blue staining was used as the loading control (H, bottom panel). Mean ± SD, n = 3 (H). J, K) Proliferation (J) and spheroid formation capacity (K) of PC3 METTL1 KO2 cells re-expressing METTL1 (WT) or catalytic dead mutant (AFPA) compared with METTL1 KO2 (eV). Mean ± SD, n = 6. L) WDR4 mRNA expression and cell growth of PC3 cells expressing doxycycline-inducible SCR shRNA or two shRNA against WDR4 with or without doxycycline induction. Mean ± SD are represented (n = 6). M) WDR4 mRNA expression and tumour growth of xenografts of cells expressing doxycycline-inducible SCR shRNA or a shRNA against WDR4 with or without doxycycline induction. Mean ± SEM are represented (n = 10 for shWD2, n = 5 for SCR, for each Dox condition). Scale bar represents 100 μm (D), 50 μm (F). Statistical tests: Two-way ANOVA (A, I, J), one-way ANOVA (C), and one-tailed Student’s t-test (B, F, K, L, M). **p < 0.01, ***p < 0.001, ****p < 0.0001., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 8: Supplementary Figure S8. Immune cell characterisation and correlation with METTL1 expression in human PCa. A) Complete cytokine array analysis of PC3 METTL1 KO compared to WT cells’ c.m. shows differential expression of inflammatory cytokines. Mean ± SD of log2 fold change, n = 4. B) tSNE analysis of the expression markers of M1-, M2-like and Mø macrophages exposed to PC3 METTL1 KO and WT cells’ c.m. of a second biological replicate (KO2 and WT2). C) Phagocytic capacity of macrophages exposed to PC3 METTL1 KO and WT cells’ c.m. Mean ± SEM, n = 3. D) Polarisation of primary peripheral blood monocytes (PMBCs) exposed to PC3 METTL1 KO and WT cells’ c.m. The upper panel shows a schematic of the workflow used. The lower panels show the quantification of the percentage of positive cells. n = 3 technical replicates of 2 biological replicates. E) Activation of T cells from a second blood donor and co-culture with macrophages exposed to PC3 WT and METTL1 KO cells’ c.m. T cells were stained with CFSE on day 0 and measured on day 3. Means ± SD, n = 3 for two biological replicates. F) Representative immunohistochemical staining for METTL1 and CD86 (M1-like macrophages), CD163 (M2-likemacrophages), and CD8 T cells in human PCa biopsies. The scale bar represents 50 μm. G, H) METTL1 mRNA expression inversely correlates with M1-like macrophage infiltration using the CIBERSORT deconvolution algorithm with TCGA and Taylor datasets (G), and TAM infiltration analysed using TIMER (H). Statistical tests: One-tailed t-test: *p < 0.05, **p < 0.01, ***p < 0.001 (D, E), Pearson’s correlation (r), p-value (pV), and linear regression with 95% confidence (bands) are shown (G, H)., Consejo Superior de Investigaciones Científicas (España), Peer reviewed

Additional file 9: Supplementary Figure S9. Characterization of Mettl1 deletion in murine PCa. A) Schematic overview of Mettl1 systemic knockout and Mettl1flox/flox mouse model generation. B) mRNA levels of Mettl1 in prostatic tissue from five-month-old Pten-KO/Mettl1+/+, Pten-KO/Mettl1+/-, and Pten-KO/Mettl1fl/fl mice. Mean ± SD, n=3. C) 5’tRNA fragment accumulation in Pten-KO/Mettl1+/+, Pten-KO/Mettl1+/- and Pten-KO/Mettl1fl/fl tumours. The right bar chart shows means ± SD, n ≥5. D) Haematoxylin and eosin staining of Pten-KO/Mettl1+/+, Pten-KO/Mettl1+/-, and Pten-KO/Mettl1fl/fl tumour sections from the ventral, dorsal, and anterior lobes. E) Representative images of immunostained sections for METTL1 and markers of proliferation (Ki67), M1-like (iNOS) and M2-like (CD68, Arg1) macrophages, and CD8+ T cells (CD8) from Pten-KO/Mettl1+/+, Pten-KO/Mettl1+/-, and Pten-KO/Mettl1fl/fl prostate tumours. Arrows indicate positive cells. F) Prostate tumour volume from Pten-KO/Mettl1+/+ and Pten-KO/Mettl1+/- five-month-old mice reflects reduced tumour burden after Mettl1 deletion. Ventral (V), dorsal (D) and anterior (A) lobes. Mean ± SD, n≥3. G) Systemic deletion of Mettl1 resulted in reduced tumour proliferation (Ki67+ cells) and increased immune infiltration of iNOS+ (M1-like) macrophages and CD8+ T cells. Staining of tumours from Pten-KO/Mettl1+/+ and Pten-KO/Mettl1+/- five-month-old mice. Mean ± SD, n≥3, >10 images per biological replicate. H) Tumour growth of allografts derived from Pten-KO/Mettl1+/+ and Pten-KO/Mettl1flox/flox tumour cells injected into NSG male mice reflects not significant tumour formation reduction in the absence of Mettl1. Mean ± SEM, n=9. I) Prostate lobe volumes in Pten-KO/Mettl1flox/flox (fl/fl) mice and Pten-KO/Mettl1+/+ (+/+) mice treated with anti-CD8 antibodies or IgG control. Mean ± SD, (n≥6). J) Prostate lobe volumes in Pten-KO/Mettl1flox/flox (fl/fl) mice and Pten-KO/Mettl1+/+ (+/+) mice treated with anti-PD1+anti-CTLA4 antibodies or IgG control. Normal prostate lobe volumes (from wild-type mice) are also shown. The bar chart on the left shows the volume in separated lobes. The bar chart on the right shows the sum of the volume of all lobes. Mean ± SD, (fl/fl and +/+ n≥6; Normal n=5). Scale bars represent 10 mm (D), 50 μm (E). Statistical tests: One-tailed Student’s t-test (G), Mann-Whitney test (C, F, H, I, J), *p<0.05, **p<0.01, ***p<0.001., Consejo Superior de Investigaciones Científicas (España), Peer reviewed