BUSCADOR RECOLECTA

Explanation note: table S1. Definitions of the response variables used to classify impact types on native species (i.e. individuals of the same taxon) and communities (i.e. individuals of several species at a site). table S2. Publication level information in PLANTIMPACTSEUROPE_publicationLevel. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. table S3. Invasive plant information and field studies testing for impacts in PLANTIMPACTSEUROPE_impactsDatabase. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. Storage location and medium: The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. (1) PLANTIMPACTSEUROPE_publicationLevel. xlsx: 266 publications with indication of countries, habitats and study locations, 312 entries (rows excluding the header), 8 columns, 59 KB. (2) PLANTIMPACTSEUROPE_impactsDatabase. xlsx: 4259 impacts (rows excluding the header), 16 columns, 348 KB., This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited., Peer reviewed

(A) Above: Sequence motif enriched in C. elegans HE cluster HMT promoters, relative to other HMTs promoters. Below: previously reported EFL-2 binding motif. (B) Binding of the C. elegans Retinoblastoma orthologue LIN-35 upstream of the TSS of the HE cluster, other HMT genes, and random genes; p-values from Wilcoxon test. (C) Enrichment for transcription factor binding, from ENCODE ChIP-seq experiments, upstream of human HMT genes. Odds ratios and p-value derived from Fisher’s exact test. (D) Boxplots show median total HMT or NNMT expression percentile drawn from 1,000 iterations of pan-cancer sampling of tumours with wild-type RB1 or potentially deleterious RB1 mutations; p-value derived from t test. (E) Total HMT expression in small cell lung cancer cell lines from the CCLE with wild-type RB1 or deleterious RB1 mutations; p-value derived from t test. (F) Estimated E2F1 activity vs. total HMT expression (both corrected for confounders) in breast cancer primary tumours from the TCGA. (G) Potential architectures of the GRN linking RB1, NNMT, and HMTs. (H) Linear model t-values explaining total HMT and NNMT expression for RB1 mutation status as the sole explanatory variable or jointly considered with NNMT/HMT expression respectively; p-value derived from t test. Underlying data for all panels can be found in https://zenodo.org/record/8383542. CCLE, Cancer Cell Line Encyclopedia; GRN, gene regulatory network; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; Rb, Retinoblastoma; TCGA, The Cancer Genome Atlas; TSS, transcription start site., Peer reviewed

(A) Boxplot shows t-values from linear mixed effects model for sample PEMT expression predicting ChIP-seq signal for various histone marks (label left) on gene bodies, promoters or repetitive elements (subpanel headers) in patient tissue samples collected as part of the ENCODE project. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. (B) Heatmap showing H3K4me3 ChIP-seq signal (log2 fold change over input) over 1,000 random genes for 4 samples from the squamous epithelium of the esophagus arranged in order of PEMT expression. (C) Boxplot shows t-values from generalised linear models for NNMT expression (RNA-seq) predicting ChIP-seq signal for various histone marks (label left) on gene bodies and promoters in cell lines of the NCI60 cancer cell line panel. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. (D) Boxplot shows t-values from generalised linear models for NNMT expression (RNA-seq) predicting ChIP-seq signal for various histone marks (label left) on different classes of repetitive elements in cell lines of the NCI60 cancer cell line panel. The number of individual sites is noted on the plot for each boxplot; p-values derive from paired Wilcoxon tests against a null distribution calculated by the mean t-value at each locus for 1,000 random expressed genes. Sites shown are from bin with highest ChIP signal (cf. S9D Fig). Underlying data for all panels can be found in https://zenodo.org/record/8383542. HERVs, human endogenous retroviruses; LINEs, long interspersed nuclear elements; LTRs, long terminal repeats; NNMT, nicotinamide N-methyltransferase; SINEs, short interspersed nuclear elements., Peer reviewed

(A) Analysis showing rank percentile position of total HMTs among correlations of NNMT expression to 56,200 genes and vice versa in 48 distinct healthy tissue types from the GTEx project. Bubble size is inversely proportional to the log of the “relative reciprocal score,” the sum of squares of the ranks of total HMTs/NNMT in the reciprocal distribution (see Methods). The dashed grey box indicates correlations in the strongest 2.5% of anticorrelated genes, with tissues labelled. (B) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 56,200 genes in a pan-cancer analysis of GTEx primary tumours across 48 tissue types. HMT-encoding genes are shown as points coloured according to association with transcriptional regulation; correlation for total HMT expression is shown as a black point. (C) Analysis showing rank percentile position of total HMTs among correlations of PEMT expression and vice versa in healthy tissue types from the GTEx project. Bubble size and dashed grey box as in panel 2A. (D) Volcano plot showing Spearman’s correlation and FDR for expression of PEMT vs. 56,200 genes in a cross-tissue analysis of 18 tissue types with a strong HMT-PEMT relationship (within the grey box in panel 2C). HMT-encoding genes are shown as points as in panel 2B. (E) Violin plot showing Spearman’s correlation to PEMT of HMTs (black, right) or other genes (left, grey) in 375 patient samples from the gastroesophageal junction. HMT-encoding genes are shown as points as in panel 2B. (F) Spearman’s correlation vs. PEMT expression of total expression of pooled HMTs added to the pool in a random order in a cross-tissue analysis of tissues with a strong HMT-PEMT relationship (within the grey box in panel 2C); 1,000 individual iterations are shown as black lines, with Loess fit trendline in red. (G) Analysis showing rank percentile position of total HMTs among correlations of PEMT expression to 60,489 genes and vice versa in 33 cancer types from the TCGA. Bubble size and dashed grey box as in panel 2A. (H) PEMT sequentially methylates phosphoethanolamine to produce PC, converting 3 molecules of SAM to SAH. (I) Analysis showing rank percentile position of HMTs classified by their substrate histone lysine residues among correlations of NNMT expression and vice versa in cancer types from the TCGA. Bubble size and dashed grey box as in panel 2A. (J) Analysis showing rank percentile position of HMT sets methylating distinct histone lysine residues among correlations of PEMT expression to 56,200 genes and vice versa in a pan-tissue analysis of 18 tissue types from the GTEx with a strong HMT-PEMT relationship (within the grey box in panel 2C). Bubble size and dashed grey box as in panel 2A. (K) Analysis showing rank percentile position of HMT sets methylating distinct histone lysine residues among correlations of PEMT expression and vice versa in a pan-cancer analysis of 7 cancer types from the TCGA with a strong HMT-PEMT relationship (within the grey box in panel 2G). Bubble size and dashed grey box as in panel 2J. (L) Violin plot showing healthy tissue sample PI, a measure of proliferation inferred from sample RNA-seq gene expression data, for 48 tissue types of the GTEx arranged by the strength of the anticorrelating relationship between PEMT and total HMTs. Note the x axis is inverted as a lower relative reciprocal score indicates a stronger relationship. (M) Violin plot showing tumour PI for 31 cancer types of the TCGA arranged by the strength of the anticorrelating relationship between NNMT and total HMTs. Underlying data for all panels can be found in https://zenodo.org/record/8383542. FDR, false discovery rate; GTEx, Genotype-Tissue Expression; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; PC, phosphatidylcholine; PI, proliferative index; SAH, S-adenosyl homocysteine; SAM, S-adenosyl methionine; TCGA, The Cancer Genome Atlas., Peer reviewed

(A) Volcano plot showing Pearson’s correlation and FDR for 225 metabolites to total HMT expression (total RNA-seq median of ratios-normalised pseudocounts) across 927 cancer cell lines from the CCLE. (B) Volcano plot showing Pearson’s correlation and FDR for expression of 10,275 expressed genes to levels of 1MNA across 927 CCLE cancer cell lines. The top and bottom 2.5% of points are shown in darker grey. HMT-encoding genes are shown as points coloured according to their association with transcriptional activation (green), repression (magenta), or an unclear relationship (blue). Pearson’s r for total HMT expression is shown as a black point. (C) PCA of metabolite levels across 927 cancer cell lines from the CCLE. 1MNA is highlighted with a red circle. (D) NNMT and HMTs both convert SAM to SAH and so can affect cellular methylation potential by acting as a “sink.” (E) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 52,440 genes in a pan-cancer analysis of 927 CCLE cell lines across 23 cancer types. HMT-encoding genes are shown as points as in panel 1B. (F) Volcano plot showing Spearman’s correlation and FDR for expression of NNMT vs. 60,489 genes in a pan-cancer analysis of TCGA primary tumours across 33 cancer types. HMT-encoding genes are shown as points as in panel 1B. (G) Violin plot showing Spearman’s correlation to NNMT for HMTs (black, right) or other genes (left, grey) in 79 primary ACC tumours from the TCGA. Individual HMT-encoding genes are shown as points as in panel 1B. (H) Spearman’s correlation vs. NNMT expression of total expression of pooled HMTs added to the pool in a random order, and 1,000 individual iterations are shown as black lines, with the locally estimated smoothing (Loess fit) trendline shown in red. (I) TCGA pan-cancer analysis showing rank percentile position of total HMTs among correlations of NNMT expression to 60,489 genes and vice versa in 33 distinct cancer types. Bubble size is inversely proportional to the log of the “relative reciprocal score,” the sum of squares of the ranks of total HMTs/NNMT in the reciprocal distribution. The dashed grey box indicates correlations in the strongest 2.5% of anticorrelated genes. Underlying data for all panels can be found in https://zenodo.org/record/8383542. 1MNA, 1-methylnicotinamide; ACC, adrenocortical carcinoma; CCLE, Cancer Cell Line Encyclopedia; FDR, false discovery rate; HMT, histone methyltransferase; NNMT, nicotinamide N-methyltransferase; SAH, S-adenosyl homocysteine; SAM, S-adenosyl methionine; TCGA, The Cancer Genome Atlas., Peer reviewed

Individual HMT levels in Rb-mutant tumours in TCGA., Peer reviewed

File List: Fig 1 F1b: Size histogram of Ba40Dy60 NPs F1c: EDX spectrum of Ba40Dy60 NPs F1e: Size histogram of Ba51Dy49 NPs F1f: F1c: EDX spectrum of Ba51Dy49 NPs Fig 2 F2: Experimental XRD patterns of Ba40Dy60 and Ba51Dy49 samples Fig 3 F3b: XRD patterns of the precipitates obtained in the conditions used for the synthesis of Ba51Dy49 NPs but using different aging times F3c: Unit cell parameters and Ba/(Ba+Dy) ratio of the precipitates versus aging time Fig 4 F4a: DLS intensity curves of the Ba51Dy49 NPs suspended in water after different periods of time at rest F4b: FTIR spectrum of the Ba51Dy49 NPs Fig 5 F5g: Total number of cells per well after exposure to increasing concentration of NPs F5h: Percentage of dead cells after exposure to increasing concentration of Ba51Dy49 NPs. F5i: MTT assay of cells exposed to increasing concentration of Ba51Dy49 NPs Fig 6 F6a: 1/T2 values obtained in aqueous suspensions of Ba51Dy49 NPs at 9.4 T and 1.44 T versus Dy concentration of the suspensions Fig 7 F7b: X-ray attenuation at 80 kVp, in Hounsfield Units (HU), of aqueous suspensions containing Ba51Dy49 NPs and Iohexol, versus suspension concentration. F7c: X-ray attenuation, in HU, of aqueous suspensions containing 20.0 mg·mL-1 of Ba51Dy49 and DyF3 NPs, versus working voltage, Bimodal medical imaging based on Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) is a well-known strategy to increase diagnostic accuracy. The most recent advances in MRI and CT instrumentation are related to the use of ultrahigh magnetic fields (UHF-MRI) and different working voltages (spectral CT), respectively. Such advances require the parallel development of bimodal contrast agents (CAs) that are efficient under the new instrumental conditions. In this work, we have synthesized, through a precipitation reaction from a glycerol solution of the precursors, uniform barium dysprosium fluoride nanospheres with cubic fluorite structure, whose size was found to depend on the Ba/(Ba+Dy) ratio of the starting solution. Moreover, irrespective of the starting Ba/(Ba+Dy) ratio, the experimental Ba/(Ba+Dy) values were always lower than those used in the starting solutions. This result was assigned to a lower precipitation kinetics of barium fluoride compared to dysprosium fluoride, as inferred from the detailed analysis of the effect of reaction time on the chemical composition of the precipitates. A sample composed of 34 nm nanospheres with a Ba0.51Dy0.49F2.49 stoichiometry, showed a transversal relaxivity (r2) value of 147.11 mM-1·s-1 at 9.4 T and gave a high negative contrast in the phantom image. Likewise, it produced high X-ray attenuation in a large range of working voltages (from 80 KVp to 140 KVp), which can be attributed to the presence of different K-edge values, high Z elements (Ba and Dy) in the nanospheres. Finally, these nanospheres showed negligible cytotoxicity for different biocompatibility tests. Taken together, these results show that the reported nanoparticles (NPs) are excellent candidates as UHF MRI/Spectral CT bimodal imaging CAs., This publication is part of the I + D + I Grants PID2021-122328OB-I00 and PID2020-118448RB-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This work was supported as well by Junta de Andalucía under grant no. P20_00182, co-financed by EU FEDER funds. High-field relaxivity measurements were performed at the ICTS “NANBIOSIS”, specifically in Unit 28 at the “Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina (IBIMA Plataforma BIONAND)”., Peer reviewed

Figure S1. Height of snow (HS) monthly variation at 1500 m for the historical climate period (1980 – 2019) and different increments of temperature (colors) grouped by sector and precipitation changes (boxes).-- Figure S2. Height of snow (HS) monthly variation at 1800 m for the historical climate period (1980 – 2019) and different increments of temperature (colors) grouped by sector and precipitation changes (boxes).-- Figure S3. Height of snow (HS) monthly variation at 2400 m for the historical climate period (1980 – 2019) and different increments of temperature (colors) grouped by sector and precipitation changes (boxes).-- Figure S4. ROS frequency (days). Data are presented for the historical climate period (1980 – 2019) with different increments of temperature (colors), grouped by month (x-axis), elevations and sectors (boxes). Data represent the average of the simulated precipitation changes (ranging from -10% to + 10%, with increments of 10%).-- Figure S5. Average ROS rainfall amount (mm/day). Data are presented for the historical climate period (1980 – 2019) with different increments of temperature (colors), grouped by month (x-axis), elevations and sectors (boxes). Data represent the average of the simulated precipitation changes (ranging from -10% to +10%, with increments of 10%). Figure S6. (a) All days and (b) ROS days average daily snow ablation (cm/day).-- Table S1. FSM2 configuration implemented in this work.-- Table S2. ROS frequency, rainfall intensity and snow ablation average anomalies per ºC over the historical climate period.-- © Author(s) 2024. CC BY 4.0 License., Peer reviewed

The N-terminal tails of eukaryotic histones are frequently posttranslationally modified. The role of these modifications in transcriptional regulation is well-documented. However, the extent to which the enzymatic processes of histone posttranslational modification might affect metabolic regulation is less clear. Here, we investigated how histone methylation might affect metabolism using metabolomics, proteomics, and RNA-seq data from cancer cell lines, primary tumour samples and healthy tissue samples. In cancer, the expression of histone methyltransferases (HMTs) was inversely correlated to the activity of NNMT, an enzyme previously characterised as a methyl sink that disposes of excess methyl groups carried by the universal methyl donor S-adenosyl methionine (SAM or AdoMet). In healthy tissues, histone methylation was inversely correlated to the levels of an alternative methyl sink, PEMT. These associations affected the levels of multiple histone marks on chromatin genome-wide but had no detectable impact on transcriptional regulation. We show that HMTs with a variety of different associations to transcription are co-regulated by the Retinoblastoma (Rb) tumour suppressor in human cells. Rb-mutant cancers show increased total HMT activity and down-regulation of NNMT. Together, our results suggest that the total activity of HMTs affects SAM metabolism, independent of transcriptional regulation., Peer reviewed

The excel file includes different spreadsheet including, first, every stalagmite (age model, d18O and d13C, Mg/Ca and other trace elements when available) and, second, every composite record produced by ISCAM. The word document is the U-Th table with all the dates used in constructing the age models. This dataset corresponds to our manuscript published as a preprint in Climate of the Past: https://cp.copernicus.org/preprints/cp-2023-54/, Peer reviewed