dataesr/scientific-paragraphs-categorization huggingface dataset:
Stability of the TrV virions at neutral and low pH Within the pH range 7. 5-2. 0, dynamic light scattering experiments indicated that the hydrodynamic diameter of TrV (full particles) remained essentially unaltered (Fig. 7 , values indicated on the upper curve). In addition, within this pH range, the maximum fluorescence emission did not change appreciably (Fig. 7 , middle and lower curves), indicating that none of the buried tryptophans became exposed to the solvent (the fluorescent emission of TrV virions denatured in 4 M guanidinium thiocyanate showed a maximum at 358 nm; Fig. 7 ). The increase in scattered light at pH values below 4 was the consequence of particle aggregation, an observation that was confirmed by electron microscopy imaging (data not shown). The large size of the aggregates at very acidic pH values prevented the measurement of particle size.
A total of 5800 particles were boxed from four different micrographs using the x3d program  (Conway & Steven, 1999). Using the SPIDER software  (Frank et al. , 1996) , we performed classification by hierarchical clustering and obtained 17 classes by image averaging, with four significant ones. Classes showing side views represented 98 % of the particles on our images, preventing us from performing a 3D reconstruction. Cryo-TEM images and image analysis. Specimens of interest were studied by cryo-TEM according to standard methods with a JEOL 2010F field-emission gun and on a CM200 microscope (FEI), both operating at 200 kV. Images were obtained under low electron dose conditions (,10 e/A ˚2) and recorded at a nominal magnification of 40 0006 at different defocus settings ranging from 21. 2 to 24.
0 mm. Micrographs were recorded on Kodak SO-163 film and developed for 12 min in full-strength Kodak D19. Negatives were screened by optical diffraction to reject drifted or astigmatic images, and selected images were digitized on a Photoscan TD scanner (Z/I Imaging) at a step size of 7 mm, corresponding to 1. 75 A ˚per pixel at the sample. To perform the reconstruction, using the x3d program  (Conway & Steven, 1999) , approximately 5000, 2700, 2200 and 2800 particles were boxed from 25 and 15 (63) different micrographs for full and n-, e-and s-empty TrV samples, respectively. Final reconstructions were obtained with the best 1716, 695, 573 and 1434 particles (after 30 refinement cycles) for full and n-, e-and s-empty TrV 3D maps, respectively. The TrV map obtained in a previous study  (Estrozi et al.
, 2008)  was used as a starting model for the analyses. All subsequent refinements of particle origin and orientation were performed using the model-based polar Fourier transform programs  (Baker & Cheng, 1996). The program CTFMIX  (Conway & Steven, 1999)  was used to correct the contrast transfer function effects and for the final Fourier-Bessel reconstruction. The resolutions were estimated by Fourier shell correlation of the reconstructions (Fig. 4 ) from half datasets using the criterion of 0. 5 correlation  (van Heel & Schatz, 2005). The isosurface representations of the reconstructed densities were rendered using RobEM (Fig. 3 ) and Amira (Mercury Computer Systems) (Fig. S3 ). Comparison of cryo-TEM reconstructions. The cryo-TEM reconstructions were computed on orthogonal 3D grids with a spacing of 1.
75 A ˚, and the corresponding average radial densities, each sampled at 2 A ˚, were computed by taking the mean value of the density within shells that were 5 A ˚wide. The limits of the protein shell were assigned to the points where the average radial density reaches the value corresponding to the exterior of the particle (frozen solvent). The distance between these two points represented a capsid thickness of ~34 A ˚, which was identical for all reconstructions. The correlation coefficients and crystallographic R factors used for the comparison between cryo-TEM particle reconstructions and the crystallographic TrV atomic model [Protein Data Bank (PDB) 3NAP] were calculated with the URO program  (Navaza et al. , 2002)  employing the Fourier coefficients within the 200-20 A ˚resolution range.
For these calculations, the densities inside a sphere of radius 120 A ˚were set to zero in order to restrict the analysis to the region corresponding to the protein shell. All reconstructions were normalized, filtered to 22 A resolution and subtracted for display in Fig. 3. Operations with maps were computed with MAPMAN  (Kleywegt & Jones, 1996)  and the CCP4 suite of programs  (Winn et al. , 2011). Fitting the TrV X-ray structures of VP1, -2 and -3 into the cryo-TEM reconstructed densities. To implement the 'tectonic model'  (Belnap et al. , 2000) , and as described in Results, the X-ray structures of the protomer VP1-3 and of each VP were positioned onto the cryo-electron microscope reconstructed densities using VEDA (http:// mem. ibs. fr/VEDA). This software allowed the application of icosahedral symmetry to generate an entire capsid from the individually fitted protein structures, thus allowing us to discard significant clashes between neighbouring protomers.
, 2002; Garriga et al. , 2012) , and empty and full (160S) PV particles  (Lewis et al. , 1998; Levy et al. , 2010; Bostina et al. , 2011). This table summarizes the main characteristics associated with PV and HRV2 genome release together with the results reported here for TrV. EPs were prepared by heating purified virions as follows: TrV and HRV2, above 50 u C for 30 min, and PV at 50 u C for 3 min and 55 u C for 10 min for the 135S and 80S particles, respectively. LDR, low-density lipoprotein receptor; PVR, PV receptor; CDE, clathrin-dependent endocytosis; PFR, pocket factor release. emission was produced. Fluorescence spectra were obtained using a Jobin Yvon SPEX FluoroMax-3 fluorometer with an excitation wavelength of 295 nm and an emission range of 305-420 nm. Three independent measurements were interpolated using the GRAMS software.
Static light scattering data were obtained with the same equipment but with excitation at 320 nm and collection of the scattering data in the range 315-325 nm. For each sample, the mean scattering intensity was calculated. Samples were prepared in 100 mM of the corresponding buffer (Tris for pH 7. 0-7. 5; citric acid for pH 2. 0-6. 5) and were incubated for 24 h before measurement. The concentration of TrV in each condition was 0. 1 mg ml 21 , determined using a bicinchoninic acid assay (Pierce).
ACKNOWLEDGEMENTS We thank  Guy Schoehn  and  Elizabeth Hewat  for their precious advice and comments. J. A. was awarded a short-term fellowship from  EMBO  ( ASTF 309-2008 ) for a 3-month stay under the supervision of E. N. at the  IBS, Grenoble. R. S. -E. acknowledges a pre-doctoral grant from the  Basque Government (BG). G. A. M. is partially supported by  ANPCyT  (PICT no. 32618/05 ), Argentina. J. N. is grateful for an  Ikerbasque fellowship  to visit D. M. A. G. 's laboratory during 2011-2012. D. M. A. G. is grateful for the support of  Bizkaia:Xede ,  UPV/ EHU (IT-461-07 ), the  BG  ( AE-2012-1-44  and  MV-2012-1-41 ),  CYTED  ( 209RT0364 ) and  MICINN  ( BFU2007-62062 ). D. M. A. G. is visiting professor at the  Basque Country University (UPV/EHU ).
We used a DNAbased approach combining the barcoding concept and Illumina next-generation sequencing to (i) describe the species diet across its entire range and (ii) evaluate the influence of landscape heterogeneity on diet diversity and composition. Faeces from 96 individuals were sampled across the entire species range and their contents were analyzed using the trnL metabarcoding approach. In parallel, we built a large DNA reference database based on a checklist of the plant species of the Daraina region. Our results suggest that golden-crowned sifakas exhibit remarkable dietary diversity with at least 130 plant species belonging to 80 genera and 49 different families. We highlighted an influence of both habitat type and openness on diet composition suggesting a high flexibility of foraging strategies.
Beyond environmental changes and the associated feeding behavior flexibility of species, it is important to stress that, due to these practical difficulties, little is actually known about the feeding behavior of most species. The emergence of nextgeneration sequencing (NGS) technologies combined with the massive expansion of animal and plant barcode databases  [26, 27]  has recently allowed to perform diet analysis by identifying the DNA sequences of consumed items from faecal material, without the need of laborious and expensive steps of cloning of PCR products  [28, 29, 30]. These powerful and non-invasive methods can provide accurate dietary profiles for several tens or hundreds of individuals simultaneously and result in extended knowledge on the foraging ecology at a population scale.
This suggests that the species may cope with various environmental conditions and resources and has a very plastic response to landscape heterogeneity. The first aim of our study was to describe the diet of goldencrowned sifaka in terms of plant taxa using a DNA-based approach combining barcoding and next-generation sequencing  [30]  to compare our results with those published by Meyers  [34]. We conducted this study in the dry season which, according to Meyers  [34] , is the period of lowest availability of the sifaka's preferred food items (seed, fruits, immature leafs). We carried out a comprehensive sampling of sifaka fresh faecal pellets across the entire species range and in parallel built a large DNA barcoding reference database from a checklist of plants of the Daraina region. Our second aim was to use co-inertia analysis to explain the relationship between the spatial patterns of diet diversity and composition and the local environmental heterogeneity, expressed in terms of habitat types and openness.
Habitat characterization Landscape structure was described using a GIS, with a 30630 m grid cell size, constructed using a Landsat images taken in 2002 (April 15 and May 27). We used the Normalized Difference Vegetation Index (NDVI), calculated as follow: (NIR-Red)/(NIR+Red) (where NIR is TM4) to remove shade effects, the area of interest being in a hilly landscape. The vegetation map (performed by CC, LG, LN and PR) was obtained by automatic classification of five channels of LANDSAT with 56 classes using the module ISOCLUSTER from the IDRISI computer program (Clark Labs). The classes corresponding to the same types of vegetation were then regrouped to obtain 30 classes. Field knowledge and observations, aerial images from 1949 and 1992 and very high resolution data for part of the area (SPOT imagery, QuickBird Imagery from Google Earth) were used to control the reliability of the classification and improve its accuracy.
We amplified the P6 loop region of the trnL (UAA) intron  [41]  using the universal primers g (59-GGGCAATCCTGAGCCAA-39) and h (59-CCATT- GAGTCTCTGCACCTATC-39) modified by the addition of specific tags on the 59 end to allow the assignment of sequence reads to the relevant sample  [30]. All the PCR products were tagged identically on both ends. These tags were composed of CC on the 5' end followed by nine variable nucleotides that were specific to each sample. The nine variable nucleotides were designed using the oligoTag program (http://www. prabi. grenoble. fr/trac/OBITools) with at least three differences among the tags, without homopolymers longer than two, and avoiding a C on the 5' end. All the PCR products from the different samples were first titrated using capillary electrophoresis (QIAxel, QIAgen GmbH, Hilden, Germany) and then mixed together, in equimolar Seasonal variation: deciduous leaves, some sclerophyllous species.
Completion of the DNA barcoding taxonomic reference library We built a local DNA barcoding reference library of genera by retrieving the whole trnL (UAA) intron sequence from EMBL for the plant genera present in the Daraina region, using a checklist of 2039 species belonging to 654 genera and 146 families compiled by the Botanical Garden of Geneva (performed by CC, LG, LN and PR). We decided to build a local database at the genus level and not at the species level for three main reasons. First, the P6 loop region of the trnL has a relatively small size which makes it particularly suitable for analyzing diet from degraded DNA  [29]  but this leads to a relatively low resolution at the species level  [41, 42]. Secondly, a large number of species of the checklist are endemic of Madagascar and their sequences of trnL (UAA) intron are often not available in EMBL.
These samples correspond to 114 genera (of which 58% were identified to the species level) belonging to 36 different families. For each sample, a piece of leaf was preserved in silicagel gel before DNA extraction. Total DNA was extracted with the BioSprint DNA Plant Kit (Qiagen Gmbh, Hilden, Germany) following the manufacturer's instructions. DNA extracts were then amplified with universal c-d primer pair  [43]  amplifying the whole trnL (UAA) intron (c: 5'-CGAAATCGGTAGACGCTACG-3'; d: 5'-GGGGATAGAGGGACTTGAAC-3'). The PCR products obtained were sequenced on an ABI PRISM_ 3100 Genetic Analyzer (Applied Biosystems, Foster City, CA) using standard protocols  [41]. All the sequences have been deposited in GenBank (accession nos. KC479210 -KC479323). Finally, for each reference plant, the P6 loop sequences (21-132 bp) were extracted from the whole trnL (UAA) intron sequence and used to build the reference database.
Overall, the local database contained 449 genera (69% of the genera of the checklist) belonging to 112 families. Approximatively 23% of the families on the checklist are not represented in the local database, of which most endemic to Madagascar, monogeneric or bigeneric  (29 out 34). The overall discrimination rate of the database at the genus level (R g = total number of unique sequences/total number of genera in the database) was 0. 83. This means that this local database can identify without ambiguity 57% (i. e 0. 83*0. 69) of the genera present in the study area.
Sequence analysis and taxon assignation The sequence reads from faecal DNA were analyzed using OBITools and associated programs (www. prabi. grenoble. fr/trac/ OBITools). First, the direct and reverse reads corresponding to a single molecule were aligned and merged using the solexaPairEnd program, taking into account quality data during the alignment and the consensus computation. Then, primers and tags were identified using the ngsfilter program. Only sequences with perfect match on tags and a maximum of two errors on primers were taken into account. The amplified regions, excluding primers and tags, were kept for further analysis. Strictly identical sequences were clustered together using the obiuniq program, keeping the information about their distribution among samples. Sequences shorter than 10 bp, or containing nucleotides other than A, C, G and T, or with occurrence lower or equal to 10 were excluded using the obigrep program.
The sequences that meet only one of these two criteria were classified as ambiguous and were manually checked. The remaining sequences were discarded from the dataset. To assign a taxon to each of the filtered sequences, we successively used two different taxonomic reference libraries. The first database (''EMBL database'') was built by extracting all the sequences of P6 loop of the trnL intron from EMBL nucleotide library using the ecoPCR program  [44]. The second database (''local database'' -see above) included only the sequences of the plant found in the Daraina region. In both cases, the taxon assignation was achieved using the EcoTag program  [28]. EcoTag relies on Needleman and Wunsch  [45] 's dynamic programming global alignment algorithm to find highly similar sequences in the reference database.
A unique taxon was assigned to each unique sequence. This unique taxon corresponds to the last common ancestor node in the NCBI taxonomic tree of all the taxids that best matched against the query sequence. A genus name was accepted only if the best match score was equal or greater to 0. 98 or more and a family name was retained only if the maximum identity was equal or above 0. 95 or more. We did not consider the sequences with a maximum identity , 0. 9 which were likely the results of PCR artefacts (including chimeras, primer dimers or nuclear pseudogenes) or contaminations. Lastly, the list of taxa identified using the local reference database was evaluated by one of us (LN) who is a taxonomist specialist of the Daraina flora. This allowed us, in some cases, to refine, for example, the identification to a single genus when there was an ambiguity among two genera with the same DNA barcode but only one genus was likely to occur in the sampling site and/or to be consumed by sifakas.
Determinants of diet richness and composition across landscape To evaluate the efficiency of our sampling effort, we analysed the cumulated number of both unique sequences and genera in the faeces against the number of individuals sampled using accumulation models  [46]. Rarefaction curves were generated using 500 ''Mao Tau'' randomizations with EstimateS Version 8. 2  [47]. Total richness was estimated by the Chao2 estimator  [48]. We then used a multiple linear regression to model the variation of the sequence richness across the different habitats, using the proportions of the six habitat types within the home range centered on the location of the sample collection. Lastly, to measure the relationship between the diet composition and the habitat composition, we employed a coinertia analysis  [49]  (as implemented in the ade4 R package software  [50] ) between the PCA of the diet composition table (presence/absence of each food item in each sample) and the PCA of the landscape structure table.
Diet richness and composition of the golden-crowed sifakas The diet of P. tattersalli included at least 130 different plants (Table  S1 ) belonging to 80 genera and 49 different families (Table  2 ) and showed a high flexibility with an average frequency of occurrences (F o , the proportion of faeces including the MOTU) of only 9. 8 % (sd = 0. 12). This means that most plants were only found in a limited number of the individuals. Eighty plants (61% of the MOTUs) were identified to the genus level (Fig. 3c ) among which 29 are monospecific in the Daraina region (i. e. we could unambiguously assign a species name to them). Five MOTUs were identified at best at the subfamily level and 29 at the family level. The 17 remaining MOTUs (13%) were assigned to a higher taxonomic level. Importantly we found that by using both the local reference database and the expertise of a taxonomist of the Daraina flora, we improved the accuracy of the identification for 52% of the sequences and we more than doubled the number of MOTUs identified to the genus level (from 29 to 80) (see and compare Fig.
3 a, b, c ). The most consumed plant/sequence belonged to the family of Apocynaceae (with a frequency of occurrence F o of 80% and a global frequency F s of 30%). However, we could not assign a genus name to the corresponding sequence because of the weak power of resolution of the P6 loop within the Apocynaceae (the discrimination rate (R g ) of this family in the reference database is 0. 69). Indeed, this sequence matched perfectly with the P6-loop barcodes of five different genera and may correspond to either one or several of them. A similar pattern was observed in the Sapindaceae (R g = 0. 62) for which only two sequences (among the five assigned to this family) could be identified at the genus level. Overall, six MOTUs could not be assigned to the genus level because of an ambiguity between two genera showing exactly the same P6-loop barcode.
Improving the level of completeness of reference databases is probably the most critical issue in DNA-based diet analyses. We are conscious that building exhaustive species databases is probably out of reach in tropical forests  [59]  due to the often high diversity of the flora and the hard and challenging taxonomic work (less than two-thirds of the plants collected for this study could be identified at the species level). However, we think that particular attention should be paid to obtaining representative databases at least at the family level to limit misidentifications or unrecognized sequences. For instance, none of the trnL sequence of the family Physenaceae (endemic of Madagascar) was available in the public databases. Consequently, when we assigned the taxon names using the EMBL database only, we removed by mistake a DNA sequence of this plant family because its maximum identity (0.
81) was below our exclusion threshold (i. e. ,0. 9). There are also cases where the public database may help in identifying the sequences that would not be assigned (and hence discarded) by using the reference databases. This happens when the plants are not known to exist in the study area but actually do  [42]. In our study, the public database enables the identification of numerous cultivated or introduced plants that were not reported in the checklist of the taxonomists. A limitation of this approach is the accuracy of the identification of the P6-loop barcode which was found to differ strongly between plant families and does not always allow us to reach the genus level. This marker presents numerous advantages: it has a small length and can be easily amplified despite the high DNA degradation in faecal samples and a large taxonomic coverage (i.
Acknowledgments The field work was possible thanks to the support of the  NGOs FANAMBY  (in particular  S. Rajaobelina ,  S. Wohlhauser , and  McG. Ranaivo Arivelo ). We warmly thank the  Daraina local communities  for welcoming us,  J. Salmona ,  A. Besolo , all guides and research assistants for their precious help on the field and  Greg King  for his help in improving the English. We gratefully acknowledge  P. Lowry ,  A. Kuhlman  from the  Missouri Botanical garden ,  R. Spichiger ,  P-A Loizeau ,  E. Roger ,  C. Rajeriarison  and the  Departement de Biologie et Ecologie Vegetale de l'Universited'Antananarivo  for supporting the botanical part of the project. We also thank all taxonomists who identified herbarium specimens. We thank the  GDRI-BDDM ''Biodiversiteet Developpement Durable aMadagascar''  and  CAFF/CORE , the '' Direction generale des Eaux et Foret '' for giving us permission to conduct the fieldwork in Madagascar and for the authorizations to export the samples.
The lab work was partly funded by the  Institut Francais de la Biodiversite, Programme Biodiversitede l'Ocean Indien  (reference no. CD-AOO1-07-003 ) and by  Laboratoire d'Excellence (LABEX)  entitled  TULIP  ( ANR-10-LABX-41 ). LC was also partly funded by the  FCT  grant  PTDC/BIA-BEC/100176/2008. PR, LG, LN, and CC were supported by the  Conservatoire et Jardin botaniques de la Ville de Geneve, Conservation International (CBC fund) , the  Fondation Jean-Marcel Aubert  and the  Vontobel Stiftung. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Patients Since 2008, 419 patients affected by ataxia of unknown etiology with cerebellar atrophy whose DNA was sent to the diagnostic center were screened for ADCK3 mutations (Dr Anheim and Dr Koenig). Biallelic mutations were found in nine patients (all but patient #7). Molecular diagnosis was made after ubiquinone deficiency was evidenced in patient #7 (Dr Rötig, Dr Lebre, Dr Desguerre, Dr Pascale de Lonlay). All samples were collected under informed consent. In addition on the ten patients, we retrospectively reassessed clinical data from four previously reported patients  [4, 5, 7]  and provide an update of the outcome thanks to their referral neurologists. Patient #11 has been reported as patient 7 in  [4] , patient #12 as patient 4 in  [5, 7] , and patients #13 and #14 as patients 2 and 3, respectively, in  [5].