dataesr/scientific-paragraphs-categorization huggingface dataset:
Total RNA was isolated and, after cDNA preparation, emplk1 gene specific PCR was carried out on serial dilutions. As shown in Figure  2 , emplk1 transcripts could be clearly identified in all larval stages tested, and particularly prominent expression was observed in primary cell cultures, which typically contain large proportions of parasite stem cells  [13, 14]. During the E. multilocularis genome project, preliminary deep sequencing transcriptome data were generated for primary cell cultures (2 and 11 days old) as well as for metacestode vesicles and activated/dormant protoscoleces  [28]. When we analyzed these profiles we found particularly high expression in primary cell cultures after 2 days of cultivation, which was reduced in primary cells after 11 days, and basal in metacestode vesicles and protoscoleces (Figure  S1 ).
Furthermore, germinal Figure  1. Amino acid sequence and structural analysis of EmPlk1. The EmPlk1 amino acid sequence was aligned to Plk1-like enzymes of S. mansoni (SmPlk1; GenBank accession number: AY747306), Homo sapiens (Plk1; P53350); D. melanogaster (Polo; P52304) and X. laevis (Plx1; P70032). The predicted kinase domain is boxed, predicted Polo-boxes (Polo-box 1; Polo-box 2) are indicated above the alignment. Residues identical in at least four of the sequences are shown in white on black background. The eleven sub-domains known to be highly conserved in kinases are indicated above (I-XI). Highly conserved amino acid residues and sequence motifs are indicated above the alignment. The highly conserved threonine residue which is critical for activation is marked by (T*) above the alignment.
BI 2536 affects metacestode development from stem cells Having established that the PLK inhibitor BI 2536 affects the enzymatic activity of EmPlk1, we next investigated whether this compound could also inhibit the formation of metacestode vesicles from parasite stem cells. To this end, we set up Echinococcus primary cell cultures and measured the formation of mature metacestode vesicles in the presence of different concentrations of BI 2536. As shown in Figure  4 , metacestode formation was already significantly reduced in the presence of 5 nM BI 2536, while concentrations of 25 nM or higher almost completely prevented parasite development. We also tested BI 6727 in the primary cell culture system and, as BI 2536, this inhibitor prevented metacestode vesicle formation in a concentration dependent manner, although at slightly higher concentrations than BI 2536 (data not shown).
Acknowledgments The authors wish to thank  Monika Bergmann ,  Dirk Radloff , and  Arlette Lescuver  for excellent technical assistance. Ferenc Kiss  is thanked for valuable advice in bioinformatic procedures. Sequence data of the E. multilocularis genome sequencing project have been produced by the Parasite Sequencing Unit at the  Wellcome Trust Sanger Institute (Matthew Berriman)  (http://www. genedb. org/Homepage/Emultilocularis).
This work was supported by grants from the  Deutsche Forschungsgemeinschaft (DFG ;  BR 2045/4-1 ) and the  Wellho ¨fer Foundation  (all to KB), and by the  Institut de la Sante et de la Recherche Medicale and UniversiteLille Nord de France. AS and UK were supported by grants of the  German Excellence Initiative  to the  Graduate School of Life Sciences, University of Wu  ¨rzburg. MV was supported by the  Ministere de l'Education Nationale et de la Recherche, France. This publication was funded by the  German Research Foundation (DFG)  and the  University of Wu ¨rzburg in the funding programme Open Access Publishing. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Annotation of reads. A BLASTN search against the nonredundant NCBI database (E value, Ͻ1eϪ5) was performed. Reads with no significant similarity to sequences stored in the NCBI database were classified as "unknown reads. " The virome taxonomic composition was estimated using GAAS  (23) , which is based on a BLASTX search against the RefSeq Viral Genomes database (E value, Ͻ1eϪ5) and normalizes the number of reads matching each viral genotype by the length of the genome. Functional annotation was performed on the MG-RAST server (24) using the nonredundant SEED database (E value, Ͻ1eϪ5). A stringent search of virulence factors was also performed using BLASTX on the Virulence Factor Database  (25) , with 60% as the minimum identity and a cutoff E value of Ͻ1eϪ5. Assembly and contig annotation.
The reads were assembled into contigs using the Newbler de novo assembler (Roche) with at least 98% identity and 35 bp of overlap. Only contigs longer than 400 bp were used in subsequent analyses. Known and unknown contigs were identified on the basis of the BLASTN search against the nonredundant NCBI database (E value, Ͻ1eϪ5). The taxonomic and functional contig classification was based on a BLASTX search against the nonredundant NCBI database (E value, Ͻ1Ϫ5). A specific search for contigs encoding antibiotic resistance genes was also performed using BLAST on the ARDB (Antibiotic Resistance Genes Database) with an E value of Ͻ1eϪ5 (26). Significant hits were manually verified. Phylogenetic trees. When possible, phylogenetic trees of the contigs encoding antibiotic resistance genes were built.
The program Prodigal was used to search for open reading frames (ORFs) in these contigs  (27). Homologs to the translated ORFs were searched against the nonredundant NCBI database using BLASTP. A multiple alignment was constructed using MUSCLE  (28)  and curated using Gblocks  (29). The phylogenetic tree was then built using the PhyML algorithm  (30)  with a bootstrap value of 100. These tasks were all performed using the pipeline freely available at www. phylogeny. fr (31). The trees were visualized using MEGA v. 4  (32). Evidence of temperate bacteriophages. Contigs generated from the assembly were analyzed to search for indicators of temperate bacteriophages, as previously described  (33). We searched for three indicators: (i) nucleotide identity to bacterial genomes (BLASTN; E value, Ͻ1eϪ5; 90% minimum identity; 90% minimum query coverage), (ii) the presence of integrase-encoding genes using annotations from the COG and PFAM databases (E value, Ͻ1eϪ5), and (iii) significant similarity to prophage proteins available on the ACLAME database (BLASTX on the ACLAME prophages database; E value, Ͻ1eϪ5).
Data were graphically represented using the R package "VennDiagram. " Comparative metagenomics. The coprolite-associated virome was taxonomically and functionally compared to 21 published viromes of modern stools from healthy adult humans  (12, 33) , which had been generated using multiple-displacement amplification (MDA), as was the case with the coprolite virome. All viromes were taxonomically (GenBank database; E value, Ͻ1eϪ5) and functionally annotated (SEED database; E value, Ͻ1eϪ5) using MG-RAST. Annotations were performed on reads using amino-acid-level comparisons. The taxonomic and functional virome profiles were compared using principal component analysis on the MG-RAST server (normalized data, Bray-Curtis measure of distance). Species richness estimations were obtained from the MG-RAST server.
Functional diversity (measured by the Shannon-Wiener index) was calculated using the "estimateDiversity" function of the ShotGunFunction-alizeR package on the SEED-based functional metagenome annotations (E value, Ͻ1eϪ5)  (34). Specific PCR amplifications and sequencing. Suicide PCR amplifications were performed to confirm high-throughput pyrosequencing results. To perform suicide PCR, the primer pairs were used only once in working areas, and no positive controls were used  (35). For giant virus detection, primer pairs targeting the nonfunctional B-family DNA polymerase were used. Additional primer pairs were designed to specifically target ORFs identified in some viral contigs assembled de novo from the virome and matching cyanophages, Mycobacterium phages, Bacillus phages, Burkholderia phages, Celeribacter phages, and Clostridium phages (see Table  S1  and Section 4 in the supplemental material).
Finally, 41. 93% of the reads were assembled into 1,464 contigs that ranged from 421 to 12,500 bp (see Table  S2 ). In total, 22. 15% of all reads and 17. 28% of all contigs were significantly similar to known sequences from public databases (Fig. 2A ; also see Table  S2 ). Genome-length normalized counts of viral reads showed that about 85. 21% and 0. 81% of viral similarities were to double-stranded DNA (dsDNA) viruses and single-stranded DNA (ssDNA) viruses, respectively (Fig. 2B ). Among the double-stranded DNA viral reads, we mostly observed Siphoviridae (58. 89%), Myoviridae (8. 79%), and Podoviridae (5. 95%). Overall, we found reads to viral families that can infect eukaryotes (Ascoviridae, Poxviridae, Iridoviridae, Adenoviridae, Mimiviridae, Herpesviridae, Baculoviridae, Polydnaviridae, and Phycodnaviridae), archaea (Lipothrixiviridae, Tectiviridae, and Bicaudaviridae), and bacteria (Siphoviridae, Myoviridae, and Podoviridae) (Fig.
2B ). Few reads showed similarities to eukaryotic viruses, and among them, those belonging to Phycodnaviridae were the most abundant (0. 81%) (Fig. 2B ). We also identified a contig encoding a hypothetical protein of invertebrate iridescent virus 3 (IIV-3). IIV-3 is a member of the Iridoviridae family, genus Chloriridovirus, which has a large particle size (180 nm) and infects mosquitoes (see Table  S3  in the supplemental material). Metagenomic results were confirmed by ad hoc suicide PCR  (35). In the presence of negative controls, a 167-bp fragment of a Mimiviridae-like nonfunctional B-family DNA polymerase was amplified and se-quenced, revealing 84% identity to that of the Moumouvirus of the Mimiviridae family (GenBank accession no. GU265560. 1). Only a small proportion of viral reads were related to viral families infecting archaea.
In particular, we detected contigs matching the tail fiber protein coding gene of cyanophage S-TIM5, the tape measure protein coding gene of Planctomyces limnophilus DSM 3776, the gene coding for an unnamed protein product of Synechococcus phage S-CB53, and a hypothetical protein coding gene from an uncultured phage identified in a viral metagenomic study of water from the Mediterranean Sea. An ORF encoding a putative phage tail fiber protein of Celeribacter phage P12053L was also identified on one of these contigs, amplified by specific PCR, and the 280-bp amplicon was verified by Sanger sequencing. However, the weak similarities shown to some of these highly shared bacteriophage genes and the database bias toward genomes of marine viruses make it difficult to state if these specific aquatic bacteriophages or other populations of bacteriophages are present in the sample.
At last, a 1,939-bp contig matched an unidentified phage previously described in a viral metagenomic study performed on modern human stools  (33)  (see Table  S3 ). Only a scaffold is available for the unidentified phage, and the matched protein is annotated as a hypothetical protein; however, this hypothetical protein is predicted to contain a conserved domain corresponding to an Nacetylmuramoyl-L-alanine amidase. This domain is characteristic of autolysins that degrade peptidoglycans and is typically observed in bacteriophage, prophage, and bacterial genomes. Evidence of a temperate life cycle for the detected bacteriophage sequences was observed using three indicators (33): (i) nucleotide identity to bacterial genomes (an indicator of prophage formation), (ii) the presence of integrase-encoding genes (markers of temperate bacteriophages), and (iii) similarity to prophage sequences available in the ACLAME database (see Materials and Methods).
We observed that 329 contigs (22. 47%) significantly matched prophage proteins in the ACLAME database, 52 contigs (3. 55%) had significant nucleotide identity to bacterial genomes (especially genomes of Escherichia coli strains), and 32 contigs (2. 18%) harbored integrase-encoding genes (see Fig. S2  in the supplemental material). This strategy provides only a minimal estimate of the number of temperate bacteriophages, as stated by Minot et al. (33). Overall, 375 contigs (25. 61%) presented at least one of the three indicators and could be tentatively classified as temperate bacteriophages (see Fig. S2  in the supplemental material). The coprolite-associated DNA virome was compared to the viromes of 21 modern human stool specimens (Fig. 4 ). At the taxonomic level, the coprolite virome did not group with modern stool viromes, whereas it was functionally more similar to some of the modern stool samples (Fig.
, and the BLAST-based annotation was further confirmed by a phylogenetic tree constructed from the ORF of this contig (see Fig. S3  in the supplemental material). To further investigate the presence of virulence genes, virome reads were examined using the Virulence Factor Database, which includes both conventional factors directly involved in pathogenesis and factors important to establishing infection. A stringent search allowed the identification of 166 reads encoding virulence factors. In particular, virulence factors of the bacterial genera Escherichia (n ϭ 42), Salmonella (n ϭ 39), and Shigella (n ϭ 34) were observed (see Table  S5  in the supplemental material). A pathway-centric analysis based on COG annotation revealed that virulence (defense mechanisms) was overrepresented in the coprolite compared to modern stools.
SD-OCT imaging Pupils were dilated with tropicamide (Mydriaticum, Thea, France) and phenylephrin (Neosynephrine, Europhta, France). Animals were then anesthetized by inhalation of Isoflurane (Axience, France) and placed in front of the SD-OCT imaging device (Bioptigen 840 nm HHP; Bioptigen, North Carolina, USA). Eyes were kept moisturized with 9% NaCl during the whole procedure. Image acquisitions were performed using the following parameters: Rectangular scan/1000 A-scan per B-scan/ 100B-scan 1 frame or 4B-scans 16 frames. Acquired images were saved as. avi files and processed with Fiji software (available at http://fiji. sc/Fiji). Firstly, image artifacts due to breathing movements were eliminated by using the StackReg Plugin. Then, using ''Z project'' function set to ''Sum Slices'', each movie was converted into a single image by compiling a Z-projection of all images of the movie.
Thus, the final image results from the maximum projection of sixteen or one hundred images sampled every micron, which means 16 or 100 microns retinal width depending on the selected parameter. This manipulation eliminates most of the noise observed on individual images, which helped to show very clearly the reflectance differences present at the level of the outer retina (Fig. S1 , Supporting Information S1 and S2). Thickness of retinal layers were manually measured on this maximum projection image in an axis perpendicular to the individual layers and 500 mm from the centre of the optic nerve using Fiji software  [13]. Subretinal injections. Animals were anesthetized by intraperitoneal injection of ketamine (50 mg/kg, Virbac, France) and xylazine (10 mg/kg, Bayer HealthCare, Germany), and their pupils were dilated as described previously.
Laser-photocoagulation and choroidal neovascularization (CNV) scar quantification Three-month-old male C57BL/6JRj mice were anesthetized by intraperitoneal injection of ketamine (50 mg/kg) and xylazine (10 mg/kg). Pupils were fully dilated with 1% tropicamide. Coverslips positioned on the mouse cornea were used as a contact lens. Laser-photocoagulations (400 mW, 50 ms, 100 mm spot size) were performed 1 to 2 disc diameters away from the papillae with a Laser Yag 532 Eyelite (Alcon, USA) mounted on a slit lamp (BQ 900, Hagg-Streitt, France). Laser photocoagulation and rupture of Bruch's membrane were confirmed by immediate observation of a bubble. Choroidal neovascularization (CNV) was quantified 7 days after Laser impact and reported as volume units (mm 3 ). Volumetric data obtained from SD-OCT sequences, viewed and analyzed with Imaris software (Bitplane, CT, USA) were compared to data obtained by direct measures of oblate spheroid CNV from the same SD-OCT sequences treated by FIJI software as described before.
Extrapolated volume was calculated with the following formula (4/3p*a*b 2 )/2 (in which a is the polar radius and corresponds to the measure along the vertical axis and b is the equator radius and corresponds to the horizontal axis). To determine the power of the extrapolation method compared to 3D rendering method, a linear regression was performed with GraphPad software (San Diego, USA). Histology. Animals were euthanized by CO 2 inhalation. Before enucleation, a mark with an ophthalmic cautery was made at the nasal quadrant of the cornea, so as to subsequently differentiate upper, lower, nasal and temporal quadrants. For Historesin-sections processing, eyes were fixed by immersion in 0. 5% glutaraldehyde and 4% paraformaldehyde in PBS for 2 hours, dehydrated by successive ethanol baths, and included in Historesin (Leica Microsystems, Germany).
Accuracy and reliability of SD-OCT imaging At first, we wanted to verify that the averaging technique that we used to remove most of the noise from SD-OCT images allowed us to obtain a data quantification that was at least as informative as the one obtained through histological sections. We compared SD-OCT and histological morphometric measures obtained pre-and post-mortem in the same animals. All measures were done at identical locations in SD-OCT images and in corresponding histological sections. As illustrated in Fig. 1A  and B , while SD-OCT data showed very similar thicknesses in temporal and nasal sides, more important variations could be observed in histology for the same sample. Moreover, significant differences have been observed between SD-OCT measures and histological ones for the entire retina and some individual layers (Fig.
Acknowledgments The authors wish to thank  Dr Jean-Remi Fenolland  for his help on the use of the Bioptigen 840 nm HHP,  Dr Jean Livet  for advice on image postprocessing,  Dr Bertrand Calippe ,  Sophie Lavalette  and  Luisa Riancho  for technical assistance,  Stephane Fouquet  and  David Godefroy from the ''Plateforme Imagerie'' of ''Institut de la Vision'', and Christophe Grolleau (RoperScientific)  for his technical accompaniment on Metamorph software. The rho2/2 mouse strain was kindly provided by  Dr Janis Lem ,  Tufts University, Boston.
This work was supported by grants from  Association Francaise contre les Myopathies (AFM  grant  14814 )  INSERM ANR Geno 2009  ( R09099DS ),  ANR   Programme Emergence 2012  ( ANR-EMMA-050 ), and  ERC starting Grant  ( ERC-2007 St. G. 210345 ). Adeline Berger  is a recipient of a PhD fellowship from  Association Francaise contre les Myopathies  and  Florian Sennlaub  is a recipient of contract «  Interface » from Assistance Publique-Hopitaux de Paris. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
8% agarose gels, and capillary electrophoresis in a Bioanalyser 2100 (Agilent Technologies, Les Ulis, France). The RNA was reverse-transcribed using Superscript III Reverse Transcriptase (45-0039, Invitrogen by LifeTechnologies Corp. )  [19] , according to the manufacturer's protocol. Cy3-or Cy5-labeled cDNA obtained from amoeba grown under each of the query conditions was cohybridized with Cy3-or Cy5-labeled cDNA from amoebae grown in the reference condition on EH2008 oligomicroarrays  [19, 20]. Standard dye-swap hybridizations were carried out. The EH2008 microarray is a customdesigned microarray developed by our group. It contains oligonucleotides covering the open reading frames from E. histolytica genome  [21]. After pooling data from technical and biological replicates, differential expression analysis was carried out using both a paired Student's t-test and the variance estimating method in the VarMixt software package  [22].
The raw P-values were adjusted using the Benjamini and Yekutieli method  [23] , which monitors the false discovery rate. Differentially expressed genes were considered to be those with a Benjamini and Yekutieli Pvalue ,0. 05 and a $2-fold change in expression level. Complete experimental details and data sets are available in the ''ArrayExpress'' MIAME-based database (www. ebi. ac. uk/arrayexpress/) with the accession number E-MTAB-1158.
Identification of iron-responsive-element-like structures in Entamoeba histolytica The Searching for Iron-Responsive Elements (SIREs) web server (http://ccbg. imppc. org/sires/index. html) was used to identify iron-responsive-element (IRE)-like sequences in the set of E. histolytica mRNAs. The server's predictions have high, medium, and low levels of stringency. High-and mediumstringency predictions are mainly based on IREs that have been well characterized in vivo and/or in vitro, whereas low-level stringency predictions are based on mRNAs that interacted with novel iron-regulatory proteins (IRPs) in a recent genome-wide study. Some of these predictions have been validated in vitro but not in vivo  [24]. The SIREs program also considers other criteria, including the motif type, apical loop, the nucleotide at position 25, the number of UG pairs, and the free energy of the stem-loop structures.
Identification of IRE-like sequences By taking advantage of existing bioinformatics approaches, we screened E. histolytica's entire genome for post-transcriptional regulatory elements controlling cellular iron homeostasis. In eukaryotes, key proteins involved in iron transport and storage (e. g. , TfR1 and ferroportin) are regulated post-transcriptionally by cis elements present in their mRNA. These IREs are stem-loop structures containing the canonical sequences required to bind IRPs. Iron-responsive elements have been found in both the 59 and 39 untranslated regions (UTRs) of mRNAs and also in regions coding for proteins involved in iron transport and storage  [51] [52] [53]. We used the SIREs web server to identify potential IRE structures in the E. histolytica transcripts identified by the microarray analysis  [24].
We analyzed the 59-UTR, 39-UTR and coding mRNA sequences extracted from the E. histolytica genome. The results were then categorized into SIREs' three stringency levels and the presence of putative IRE-like stem-loop structures was determined by inspection of the SIREs output files. In the wholegenome analysis, we identified 550 transcripts containing IRE structures. Of these transcripts, 173 had high-or mediumstringency IREs, which were more present in coding regions than in 59-and 39-UTRs. Eighteen transcripts with putative IREs appeared to be significantly regulated in our microarray analyses (Table  7 ). Five of the latter had IRE-like structures with high and medium stringency levels. The proportion of differentially expressed genes with IRE-containing transcripts is similar to that in the genome as a whole.
AmoebaDB ID and Genbank ID refers to the accession number of the gene in AmoebaDB (http://amoebadb. org/amoeba/) and NCBI GenBank (http://www. ncbi. nlm. nih. gov/genbank/), respectively; iron deficiency refers to the fold changes of expression level in the iron deficiency condition as compared with the normal condition; Iron def + Hb refers to the fold-change of the expression level in iron deficiency following by hemoglobin supplementation as compared with the normal condition; low iron refers to the fold-change of expression level in low iron as compared with the normal condition; Please see methods for definition of iron deficiency, low iron, and normal iron condition. NM: non-modulated.