dataesr/scientific-paragraphs-categorization huggingface dataset:
1 ), while the genomic datasets are in the phago-prototroph area. The assignment to the "Parasite" area in the Mollweide projection highlights a low score (<0,5) for the main trophic categories (i. e. general phagotrophy, prototrophy and photosynthesis), but does not exclude the assignment to specialised sub-categories of phagocytosis (i. e. Entamoeba or Rozella-like phagocytosis) as highlighted by the bar chart in Fig. 1. In P. brassicae (for which both genomic and transcriptomic data are available), a detailed look at the molecular signatures highlighted that nearly half (14/29) of the phagotrophy-related genes driving the genome apart from the transcriptome were associated with cilia/flagella (as per their GO term annotation, Supplementary Material 1). Within the predictive model, flagella and cilia are describers of the phago-prototrophic niche, which accommodates organisms using these structures to feed (e.
g. Choanozoa such as Monosiga brevicollis; Fig. 1 ). On the other hand, trophic predictions for the transcriptomic datasets of P. brassicae and M. ectocarpii were similar (Fig. 1 ). In P. brassicae genes associated with phagotrophic signatures in the transcriptome were linked to GO terms involving the cytoskeleton (14/40), the cytosol (6/40) and the mTOR complexes (5/40); including the GO terms TORC2 complex, Seh1-associated complex and the lysosome gene RRAGA (Supplementary Material 1). A closer look at the predicted functions highlights their potential involvement in processes such as signal transduction, cell reorganization/polarization, metabolism and cell cycle. In particular Ras GTPases, mTORC1 and mTORC2 complexes are strong descriptors of Rozella-like phagotrophic behaviour and describe nearly half (10/21) of the signatures shared between the transcriptomes of P.
Discussion In this study, by analyzing complementary lines of evidence, we demonstrate that phagocytosis is a trait that phytomyxean parasites conserved from free-living Rhizarian ancestors, adapting it to the intracellular environment where it underpins the biotrophic interaction and where it coexists with specialized strategies of host manipulation. Molecular signatures of phagocytosis are present in all phytomyxean datasets analysed; but the model aggregates datasets in different trophic modes according to genome-based and transcriptome-based signatures (Fig. 1 ). These different predictions can be explained in the light of the polyphasic phytomyxean life-cycle  (Liu et al. , 2020) , where the transcriptome provides a realized molecular snapshot of the feeding stage whilst the genome also contains genetic information on stages other than the intracellular plasmodium (e.
, 2017) , an even higher degree of host manipulation can be expected for M. ectocarpii, bringing it even closer to its land-dwelling relative P. brassicae. Although not common, intracellular endocytosis has been documented in intracellular parasites spanning the taxa Apicomplexa  (Spielmann et al. , 2020 and references therein) , Cryptomycota  (Torruella et al. , 2018)  and Euglenozoa  (Etheridge, 2022). The reduced dataset of phagotrophy-related proteins from Rozella allomycis correctly describes Trypanosoma cruzii and Leishmania braziliensis as capable of intracellular phagotrophy  (Chasen et al. , 2020; Halliday et al. , 2020) ; whilst fails to assign Plasmodium falciparum and Toxoplasma gondii to this category. Indeed, P. falciparum and T. gondii are known to use a different set of genes to undertake endocytic nutrients uptake  (Spielmann et al.
Vector Plasmids Expressing Recombinant DENV-2 NS1 Proteins A synthetic mammalian codon-optimized gene coding for the authentic NS1 signal peptide followed by the residues NS1-1/352 of the Cosmopolitan DENV-2 strain D2-K2_RIJ059/Dar es Salaam 2014 (Genbank accession number MG189962) was synthetized by Genecust (Boynes, France). A Kozak consensus sequence for initiation of translation was inserted at the 5 end of the synthetic gene. The cloning of the synthetic gene into pcDNA3. 1 plasmid and the sequencing of the resulting plasmid pcDNA3/DES-14. NS1 were performed by Genecust (Boynes, France). Direct mutagenesis on pcDNA3/DES-14. NS1 to generate pcDNA3/DES-14. NS1-(K272), pcDNA3/DES-14. NS1-(K324), or pcDNA3/DES-14. NS1-(K272, K324) was performed by Genecust (Boynes, France). The production of endotoxin-free plasmids, the DNA quantification, and their sequencing were performed by Genecust (Boynes, France).
Immunoblot Assay Huh7 cell lysates were performed in RIPA lysis buffer (Sigma, France). All subsequent steps of immunoblotting were performed as described  [8]. Membranes were incubated with a primary antibody at dilution 1:200 and then with an anti-mouse or anti-rabbit IgG HRPconjugated secondary antibody at 1:5000 dilution. Pre-stained natural protein standards for SDS-PAGE were used to estimate the apparent molecular weights of intracellular proteins. Membranes were developed with Pierce ECL Western blotting substrate (Thermo Fisher Scientific, France) and exposed on an Amersham imager 680 (GE Healthcare, Buc, France). The signal intensity of intracellular and soluble forms of rNS1 was measured by Image J software. The results are the mean of at least three independent assays. The protein abundance of β-actin was determined and was equivalent for each intracellular form.
RT-qPCR Huh7 cells were seeded in 12-well culture plate and transfected the following day. Then, 24 h after transfection, total RNA was extracted from cells with RNeasy kit (Qiagen, Venlo, Netherlands) according to the manufacturer's instructions. Reverse Transcription was performing using M-MLV Reverse Transcriptase (Life Technologies, Les Ulis, France). Quantitative PCR was performed on CFX Connect Real-Time PCR system (Biorad Laboratories, Marnes-La-Coquette, France). Briefly, 10 ng cDNA was amplified using 0. 2 µM of each primer in SYBR Green real-time PCR master mix buffer (1X) (Thermo Fisher Scientific, Les Ulis, France). The qPCR data sets were analyzed using the ∆∆Ct method and the results were normalized to Human Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), which was used as internal control.
4 Figure 1. 41 Figure 1. Structural features of DENV-2 NS1 protein. Tridimensional structure prediction of DES-14 NS1 protein (Genbank access number MG189962) and the three mutants DES-14 NS1-(K272, K324), NS1-(K272), and NS1-(K324) was performed by modeling on PHYRE 2 protein recognition server (http://www. sbg. bio. ic. ac. uk/~phyre2/html/page. cgi?id=index; accessed on 23 December 2022). The predicted structures were analyzed with PyMOL 2. 5, a program for interactive visualization of tridimensional proteins. The colored dots indicate the positions of residues NS1-272 and NS1-324 in the 3D structure of NS1 protein.
Article https://doi. org/10. 1038/s41590-023-01642-7 ductal adenocarcinoma, ADAM12 expression was correlated with the 'stroma activated' subtype, which is associated with a severe prognosis  65  (Extended Data Fig. 8d ). We further analyzed ADAM12 expression in publicly available datasets from cohorts of patients with skin cutaneous melanoma, pancreatic ductal adenocarcinoma, prostate adenocarcinoma or colon adenocarcinoma. For each cohort, we stratified tumors by ADAM12 expression (ADAM12 expression < median expression versus ADAM12 expression > median expression). Gene Set Enrichment Analysis of pathways using the Hallmark gene sets indicated that, independently of the tumor type, ADAM12 hi tumors were significantly enriched in genes related to the terms 'Inflammatory response', 'Hypoxia' and 'Angiogenesis', and were inversely correlated  b-e, Gene set enrichment analysis (GSEA) curves for the indicated pathways for the four tumor datasets analyzed as in a (right, red square indicates the leadingedge genes).
Article https://doi. org/10. 1038/s41590-023-01642-7 with 'Oxidative phosphorylation' (Fig. 6a ), a process that requires oxygen. Pathway analysis using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) database in these tumors further indicated enrichment for the terms 'Cytokine-cytokine receptor interaction,' 'ECM-receptor interaction,' 'Tissue remodeling' and 'Regulation of wound healing' (Fig. 6a, b ). Analysis of the leading edge (i. e. , genes accounting for a pathway being defined as enriched) in the pathways 'Cytokine-cytokine receptor interaction', 'ECM-receptor interaction', 'Inflammatory response' and 'Tissue remodeling' further identified a number of shared genes in the four tumor datasets (Fig. 6b-e ), suggesting that there is a shared gene expression program across solid tumors grouped by ADAM12 expression.
Notably, and similar to the data obtained in mice models, common genes of the leading edge in the four human datasets included genes regulating or expressed by tumor macrophages, such as AXL, CSF1, CSF1R, CD14 and MSR1, and genes encoding cytokines and cytokine receptors of the OSM, IL-6 and PDGF pathways, as well as genes encoding structural and regulatory proteins of the ECM with essential roles in tissue remodeling and angiogenesis, including collagens, laminins, HSPG2, HAS2, KDR and NOX4. Consistent with increased resistance mechanisms, stratification of human prostate cancer by ADAM12 expression further correlated with the Gleason score, which identifies high-grade tumors at high risk of recurrence (Extended Data Fig. 8f ). These data show that, in several desmoplastic tumors, including pancreatic, prostate and colon cancer, ADAM12 expression stratifies patients harboring tumors with high levels of hypoxia, inflammation, tissue remodeling and innate resistance mechanisms, as well as factors associated with a poor prognosis and drug resistance such as AXL.
Online content Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at https://doi. org/10. 1038/s41590-023-01642-7. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4. 0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Immunofluorescence Tissues were processed and stained as previously described  27. Briefly, 8-µm sections from OCT-frozen tumors were incubated in 10% bovine serum (BS) in PBS containing 0. 1% Triton X-100 (PBS-TS), followed by incubation with primary antibodies in PBS containing 1% PBS-TS overnight at 4 °C, washed and incubated for 1 h at 20 °C with secondary antibodies or streptavidin, washed, incubated with DAPI (1 µg ml -1 ) and mounted with Fluoromount-G (Southern Biotechnology Associates). Expression of Adam12 on tumor sections was detected with an RNAscope ISH assay (Advanced Cell Diagnostics), following the manufacturer's instructions. We examined slides with an AxioImager M1 fluorescence microscope (Zeiss) equipped with a CCD camera and processed images with AxioVision Zen software (Zeiss) or ImageJ software.
For intracellular IFN-γ staining, cells were stimulated in vitro for 4 h with PMA and ionomycin, or with SIINFEKL peptide (OVA), and for 2 h with Brefeldin A. Cells were incubated with the LIVE/DEAD Cell Stain Kit to exclude dead cells (Invitrogen). Cells were processed for intracellular staining using CytoFix/CytoPerm Buffer Kit (Invitrogen), according to the manufacturer's instructions. Cells were analyzed with Fortessa (BD Biosciences) and Flowjo software (Tristar) and sorted with FACS ARIA III (BD Biosciences). For cell sorting of stromal cells, dead cells d doublet cells, hematopoietic (CD45 + ) and endothelial (CD31 + ) cells were systematically gated out before selecting for positive stromal cell markers. Tumor macrophages were sorted as CD45 + CD3 -CD19 -Ly6G -SiglecF -CD11b + F480 +.
Efferocytosis assay To induce apoptosis, MO5 melanoma cells were serum starved for 2 h, irradiated with UV (UVP Crosslinker at 100 mJ cm -2 ) for 10 min and incubated overnight in complete medium. Apoptotic MO5 cells were incubated with Amine-Reactive pHrodo Dyes (Thermo Fisher) at a concentration of 20 ng mL -1 for 30 min at 20 °C in the dark. For the efferocytosis assay, BMDMs were mixed with pHrodo-stained apoptotic MO5 cells for 30 min at 37 °C, at a 1:1 ratio, in the presence of conditioned medium from GFP + or GFP -cells, stained with antibodies anti-F4/80 and analyzed with Fortessa (BD Biosciences) and Flowjo software (Tristar). The fold changes on the y axis were calculated using the percentage of efferocytosis in control medium as the baseline.
RNA Isolation and qRT-PCR For total tissue RNA extraction, we used the PureLink RNA Mini Kit (Invitrogen), according to the manufacturer's instructions. To extract RNA from cells, we used FACS to sort cells, or collected cells from culture plates, and placed them directly into vials containing lysis buffer. We isolated RNA using the Single Cell RNA Purification Kit (Norgen), according to the manufacturer's instructions. We assessed the quality https://doi. org/10. 1038/s41590-023-01642-7 of total RNA using the 2100 Bioanalyzer system (Agilent Technologies) and the quantity using the Qbit RNA HS kit (Thermo Fisher). Total RNA was transcribed into complementary DNAs using SuperScript IV Reverse Transcriptase (Invitrogen). We performed qRT-PCR using RT 2 qPCR primer sets (SABiosciences and Bio-Rad Laboratories, a list is provided in Supplementary Table  2 ) and SYBR-Green master mix (Bio-Rad Laboratories), on a PTC-200 thermocycler equipped with a Chromo4 detector (Bio-Rad Laboratories), and analyzed data using Opticon Monitor software (Bio-Rad Laboratories).
RNA sequencing Librairies were prepared from total mRNA using the SMARTer Stranded Total RNA-Seq Kit v2-Pico Input Mammalian (Takara Bio), according to the manufacturer's instructions. Library quality and quantity were assessed using the 2100 Bioanalyzer system (Agilent Technologies) and the Qbit dsDNA HS kit (Thermo Fisher). Sequencing was performed using Illumina NextSeq 500/550 High Output kit v2. 5. The RNA-seq analysis was performed with Sequana 0. 11. 0 (https://github. com/sequana/ sequana_rnaseq) built on top of Snakemake 6. 1. 1 (ref. 80). Briefly, reads were trimmed from adapters using cutadapt 3. 4, then mapped to the genome assembly GRCm38 from Ensembl using STAR 2. 7. 3a. Feature-Counts 2. 0. 1 was used to produce the count matrix, assigning reads to features using corresponding annotation GRCm38_92 from Ensembl with strand-specificity information.
Human tumors We selected non-metastatic samples from three TCGA projects (RNA-seq analyses): skin cutaneous melanoma (SKCM), colon adenocarcinoma (COAD) and prostate adenocarcinoma (PRAD), all three in RKPM (Reads Per Kilobase Million) log 2 + 1 transformed. We also selected one International Cancer Genome Consortium (ICGC) project, pancreatic ductal adenocarcinoma (PACA_AU, array-based analysis), retrieved from Bailey et al. 83. We filtered out genes that had missing values in any of the samples or that were located in the Y chromosome locus. Each dataset was analyzed independently. For each dataset, ADAM12 hi and ADAM12 lo groups were defined according to their ADAM12 expression, either above or below median ADAM12 expression, respectively. Gene set enrichment analyses (GSEAs) were carried out using the fgsea R package.
A Wilcoxon test was used to analyze mean differences in gene expression between the ADAM12 hi and ADAM12 lo groups, and the Wilcoxon test value was used to make the gene rankings for GSEA. GSEA parameters were were: fgseaMultilevel(pathways = ('h. all. v7. 0. symbols. gmt', 'c5. go. mf. v7. 2. symbols. gmt', 'c2. cp. kegg. v7. 1. symbols. gmt', 'c5. bp. v7. 1. symbols. gmt'), stats = 'Gene rank', minSize = 5, maxSize = 500). GSEA results were displayed using the plotEnrichment function with default parameters from the fgsea package for GSEA curves. Genes accounting for a pathway being defined as enriched are refered to as 'leading edges'. These genes were shared by all four datasets. Expression levels of the leading-edge genes in our samples were displayed as a heat map using the ComplexHeatmap R package.
Cell proliferation was measured with Cell Counting Kit-8 (CCK-8; Dojindo, no. 899650), according to the manufacturer's instructions. To induce hypoxia, stromal cells were cultured in a hypoxic chamber (Whitley H35 Hypoxystation) in 1% oxygen for 72 h. The engulfing ability of macrophages was assessed by isolating the cells from tumors and incubating them for 30 min with Fluoresbrite Red microspheres (no. 18660-5, Polyscience) at 37 °C (or 4 °C for control condition), staining them with antibodies against F4/80 and analyzing them with Fortessa (BD Biosciences) and FlowJo software (Tristar). Gas6 was measured by ELISA, according to the manufacturer's instructions (Mouse Gas6 DuoSet ELISA, R&D, no. DY986). The tumor extracellular pH was assessed using pH Microelectrodes (Fisher Scientific), following the manufacturer's instructions.
Image quantification The immunofluorescence signal was quantified using ImageJ and threshold processing on high-resolution tiles that were stiched to create mosaic images of the entire tumor section or on tumor fields, obtained with an AxioImager M1 fluorescence microscope (Zeiss) and ZEN software. Tumor hypoxia was detected using the Hypoxyprobe Plus Kit, following the manufacturer's instructions, and the proportion of pimonidazole signal was measured by pixel quantification on mosaic images. The percentage of tumor perfused area was determined by normalizing Hoechst-positive area to the DAPI-positive area on mosaic images. Pericyte coverage was determined by measuring NG2/CD31 staining ratio by quantifying pixels on mosaic images of the total tumor section (all vessels in mosaic images were measured).
Acknowledgements We thank the  Cytometry Platform at the Institut Pasteur ; the  Biomics Olatform (C2RT, Institut Pasteur ; supported by  France Génomique  ( ANR-10-INBS-09 ) and IBISA) and the animal facility. We thank  B. Charbit ,  G. Faucher  and  A. Lepelletier  for excellent technical assistance, and  C. Leclerc  for the MO5 cell line. S. D. C. was funded by  La Ligue contre le Cancer and Institut Pasteur. A. O. was funded by a doctoral fellowship from  Le Ministère de l'Enseignement Supérieur et de la Recherche. The lab has received funding from the  European Research Council (ERC)   Consolidator  grant  648428-PERIF  (to L. P. ),  INSERM  (to L. P. ),  l'Institut National du Cancer (INCa  # PLBIO21-264 ) (to L. P. ), and  Institut Pasteur  (to L. P. ).
Data availability The TCGA_PAAD, TCGA_SKCM, TCGA_COAD and TCGA_PRAD dataset can be accessed at https://portal. gdc. cancer. gov/. The ICGC_PAN_AU dataset can be accessed at: https://dcc. icgc. org/. scRNA-seq data of pancreatic cancer from Peng et al. 86  are available from the Genome Sequence Archive (project PRJCA001063, https://ngdc. cncb. ac. cn/ bioproject/browse/PRJCA001063). scRNA-seq data from CRC  84  and SKCM  85  are accessible via the Gene Expression Omnibus (GEO) under accession codes GSE178341 and GSE115978, respectively. The genome GRCm38 (GCA_000001635. 9) release 102 is accessible from Ensembl (http://www. ensembl. org/Mus_musculus/Info/Index). RNA-seq data generated in this study are deposited in NCBI's Gene Expression Omnibus under accession codes GSE206794 (Depletion of ADAM12 + cells in MO5 tumors) and GSE206795 (ADAM12 + cells in MO5 tumors).
(a) Violin plot of Lrrc15 from RNASeq data in Fig. 3a (n = 4). (b) Immunofluorescence staining of Ki67 and GFP in melanomas growing in ADAM12-GFP mice. Scale bar, 50 µm. (c) Expression of the indicated genes, measured by qRT-PCR, in the indicated populations isolated by FACS from MO5 tumors at day 12, n = 3 from independent experiments. Macrophages (M), tumor cells (MO5), endothelial cells (EC). (d) Expression of Adam12, measured by qRT-PCR, in ADAM12 -PDGFRα + cells isolated from MO5 tumors, treated as indicated (n = 3). (e) Expression of Gas6, measured by qRT-PCR, in stromal cells cultured in indicated conditions (n = 3). (f) Normalized expression of Tgfb1 in normal skin and melanomas (from single cells RNAseq dataset 12 ). (g) Expression of the indicated genes, measured by qRT-PCR, as in c.
49153, median: 0). (c) Expression of ADAM12 transcripts in single-cell RNAseq from human PDAC 86 (N = 24 primary untreated PDAC tumors, 41986 cells). Clustering= All cells (see Methods). (d) tSNE representation of ADAM12 expression in human PDAC as described in Peng et al. 86 (top panel) and transcriptional signature of activated stromal PDAC subtype as described in Puleo et al. 65 (lower panel). Two-sided Pearson's Correlation Coefficient (R) was measured between ADAM12 expression and the activated stromal subtype signature (displayed in the tSNE panel). (e) Expression of the indicated transcripts in scRNAseq dataset from d. (f) Clinicopathologic characteristics of patients from the TCGA_PRAD project studied in Fig. 6. Patients (N = 455) were grouped according to their expression of ADAM12, as described in Methods.
Bioinformatics The steps of library separation, removal of Illumina adapters and first quality control were performed by Fasteris SA (see Supplementary Materials and Methods). The detailed scripts used in this study can be downloaded from https://github. com/mcamarareis/microbiome_assembly. Briefly, raw reads from each sequencing run were demultiplexed based on the 8 nucleotide tag sequences with cutadapt (version 2. 8. 1)  (Martin, 2011). The "tagged-PCR" approach we used generated half of both forward and reverse reads containing a P5 Illumina adapter and the other half a P7 adapter resulting in forward and reverse reads in both R1 and R2 files (mixed orientation). To deal with the presence of reads in mixed orientation in the R1 and R2 raw files, the demultiplexing was performed in two rounds (see details in Supplementary Materials and Methods).
For each combination of runs and demultiplexing rounds, error rates were defined using the function learnErrors and denoised using the dada function in pooled mode before being merged with mergePairs (which generated ASVs of about 373 bp). Then, all the independent processed datasets were merged in one sequence table (for each sample, reads from the two rounds of demultiplexing were summed while reads coming from the two sequencing runs were kept separate) and processed for chimera removal using the function removeBimeraDenovo, also performed in pooled mode and with a "minFoldParentOverAbundance" of 8. The parameters used at each DADA2 step are specified in the Supplementary Table  1. ASVs shorter than 366 bp and longer than 377 bp were filtered out, and the remaining ones were taxonomically assigned using IDTAXA (50% confidence threshold) with the Silva database v138  (Quast et al.
, 2015). For this, we used a comparative principal component analysis performed on the Hellinger transformed data. After consistency was confirmed (p < 0. 001 and correlation = 0. 99), independent technical replicates of each culture were merged by the sum of the number of reads of the ASVs present in the two replicates of the same culture (prevalence filter). (Saary et al. , 2017). Hierarchical cluster analysis (HCA) (method "ward. D2") was used to identify differences in the free-living prokaryotic communities by sites using the Hellinger distance (Euclidean distance of the Hellinger-transformed matrix;  Legendre & Gallagher, 2001)  using the function hclust from stats package (R Core Team, 2017). (ii) Experiment. To analyze alpha diversity dynamics of the cultures, rarefaction was performed at a read depth of 5,957 reads using the same approach as for the environmental samples.