dataesr/scientific-paragraphs-categorization huggingface dataset:
Specialization and Convergence in Intracellular Thiotrophic Symbionts. To test for deviating evolutionary patterns in the alphaproteobacterial Ca. R. santandreae symbiont, we compared its genome to those of 62 bacteria representing free-living relatives of Ca. Riegeria, parasites, nonthiotrophic mutualistic symbionts, as well as thiotrophic bacteria from other symbiotic and nonsymbiotic clades (for a list of genomes, see Dataset S1I). We analyzed the cellular processes encoded in each their genomes in a nonmetric multidimensional scaling (NMDS) ordination of the distribution of each their genes to clusters of orthologous genes (COGs) and to modules of the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Fig. 3  and SI Appendix, Supplementary Note 3). Apart from Ca. R. santandreae, the thiotrophic symbiont genomes formed a spectrum that was dependent on their genome sizes, suggesting that COG-and KEGG-based profiles and genome contents in the other symbionts with small genomes were largely convergent.
At the other end of this spectrum, the profiles of symbionts with nonreduced genomes overlapped with free-living thiotrophs such as Allochromatium vinosum and Thiocapsa marina (Dataset S1 J and K). While Ca. R. santandreae had the most similar distribution of encoded functions to vesicomyid symbionts, another group of vertically transmitted chemosynthetic symbionts, its profile stood out in the observed NMDS patterns across the categories of COGs and KEGG modules (Fig. 3  A and B, SI Appendix, Supplementary.
Ca. R. santandreae Note 3 and Fig. S14 , and Dataset S1 J and K; for a list of genomes, see Dataset S1I). Ca. R. santandreae deviated from the vesicomyid symbionts with an enrichment of genes coding for carbohydrate transport and metabolism (COG category G), lipid transport and metabolism (COG category I), and coenzyme transport and metabolism (COG category H) (Dataset S1J). We could corroborate this pattern in a comparison on the level of pathways as Ca. R. santandreae encoded 37 unique pathways that allow for flexible carbon fixation and the versatile storage of carbohydrates (Fig. 3C  and SI Appendix, Supplementary Note 3). In particular, the capabilities to synthesize long-chain fatty acids and polyhydroxyalkanoates (PHAs) as well as trehalose and glycogen underline a possible dual role of the symbionts in the Paracatenula symbiosis, where the symbionts provide large storage capacities for the association (Fig.
3C  and Dataset S1 L and M). This is in contrast to all other chemosynthetic symbioses and could be coupled to the high proportion of the total biomass that the Ca. Riegeria cells achieve in the Paracatenula consortium (9). While Ca. R. santandreae has a substantial set of unique pathways, it also shared 107 pathways with the thiotrophic symbionts with the most reduced genomes, Ca. Ruthia magnifica, and Ca. Vesicomyosocius okutanii. Besides energy conservation through sulfur oxidation, these shared pathways were largely related to biosynthesis and include carbon fixation via the CBB cycle and pathways for amino acid, nucleoside, nucleotide, fatty acid, and lipid synthesis (SI Appendix, Supplementary Note 3 and Dataset S1 L and M). These pathways represent the core functions of a nutritional chemosynthetic symbiont and reflect the strong selection based on the conserved metabolic needs of their invertebrate hosts.
In such nutritional symbioses, essential biosynthetic pathways must be retained because their loss would lead to a decrease in fitness or even the extinction of the affected host  (13, 14, 17). In contrast, a loss of catabolic pathways might not severely impact the symbionts but might, in return, even benefit the consortium as it leaves resources accessible to the host. Ca. R. santandreae Is a Major Carbon and Energy Buffer in the Paracatenula Symbiosis. Our comparative analyses showed that Ca. R. santandreae possessed and expressed an unexpectedly high number of pathways for a chemoautotrophic symbiont with a reduced genome, many connected to carbon metabolism and storage. The pathways included the synthesis of PHAs, trehalose, and glycogen (SI Appendix, Fig. S11  and Dataset S1L). We observed a large number of intracellular inclusions in the symbionts in both light microscopy and EM that caused the orange-white appearance of the trophosome region and further highlighted the symbionts storage capabilities (Figs.
S17 ). Glycogen is widely used to store energy and carbon in both bacteria and animals and is considered to be a long-term energy reserve under anaerobic conditions  (35, (62) (63) (64). Proteins for glycogen metabolism were also detected in the symbiont proteomes, although their genes were not highly expressed (Fig. 2  and SI Appendix, Figs. S3  and S4 ). We detected proteins for both biosynthesis and degradation in the same samples, suggesting a dynamic switching between synthesis and utilization, possibly distributed in subpopulations of the symbionts (Dataset S1 D and E). Unexpectedly, the disaccharide trehalose was by far the most abundant soluble metabolite measured in Paracatenula holobionts (SI Appendix, Supplementary Note 2 and Figs. S16  and S18 ). We could link the trehalose pool to the symbionts as it was not detectable in host tissue without symbionts (anterior rostrum fragments; n = 3; SI Appendix, Fig.
Like many marine invertebrates associated with thiotrophic symbionts, Paracatenula lacks a mouth and a gut and depends on its endosymbionts for essential nutrients. This was reflected in the broad genomic repertoire and the expression of amino acid, vitamin, and cofactor biosynthesis pathways in the symbiont (SI Appendix, Supplementary Note 2 and Figs. S19  and S20 ). Active export across the symbiont membrane appears to be limited as we only identified 15 export related gene products in Ca. R. santandreae, 8 of which had at least 1 transmembrane (TM) domain based on the identification using the Transporter Classification Database (TCDB) (SI Appendix, Supplementary Note 2 and Fig. S12  and Dataset S1 G-I). The main identified transporters were the Tat and Sec secretion systems that could translocate folded and unfolded proteins to the periplasm.
A Type I secretion system could export unfolded proteins across the outer membrane and in the hosting vacuoles but no secretion system for the transfer of proteins into the host bacteriocyte could be detected. Although several transporters such as secretion systems have essential functions conserved across bacteria  (66)  and might be involved in the nutrition of the host, unexpectedly only the Tat secretion system for the translocation of folded proteins was highly expressed (Fig. 2  and Dataset S1B). Given that we could not find expression based evidence of substantial export via transporters, we were surprised that we did not observe Ca. Riegeria cells undergoing lysosomal digestion in our transmission EM (TEM) analyses (n = 5 host specimens, 682 symbiont cells, 54,895 μm 2 total analyzed area) (Fig.
5  and SI Appendix, Fig. S21  and Table  S2 ). We also only identified nine lamellar bodies containing inclusions of symbiont cells in the same dataset. The absence of active bacterial degradation and the presence of few lamellar bodies suggests a low level of symbiont digestion. In contrast, lysosomal digestion of symbiont cells is readily observed in bacteriocytes of other chemosynthetic hosts, e. g. , members of the deep-sea mussel genus Bathymodiolus as well as in vesicomyid clams  (67, 68). Host gene expression indicated lysosome formation and trafficking as well as proteolysis, all likely involved in the digestion of symbiont biomass (Dataset S1N). One of the most important enzymes in the lysosomal digestion of bacterial cells are lysozymes. They are glycoside hydrolases that cleave the 1,4-beta-linkages in peptidoglycan of bacterial cell walls and lead to cell lysis.
Unexpectedly, we could not detect lysozyme transcripts in the host transcriptome  [79. 1% completeness identified by Benchmarking Universal Single-Copy Orthologs (69)], suggesting that lysozyme expression was below detection limit or absent. Several other types of digestive enzymes were expressed, such as the cysteine protease cathepsin B that has been shown to play a major role in the digestion of gut-bearing flatworms and is also expressed in the symbiotic gutless annelid Olavius algarvensis (70, 71) (Dataset S1N). Because the symbiont very likely has a peptidoglycan cell wall (Fig. 2  and SI Appendix, Supplementary Note 4), we conclude that complete symbiont cells are not the main target for the lysosomal digestion expressed in Paracatenula. This corroborates the ultrastructural observations and is in contrast to other animals with chemosynthetic bacterial symbionts.
Hosts such as the Bathymodiolus deep-sea mussels have been shown to constitutively express lysozymes that play a key role in symbiont digestion and the control of symbiont populations  (67). Our data rather suggest that the main mode of symbiont-tohost transfer is based on the release of OMVs and their digestion by the host. OMVs naturally package lipids, proteins, and sugars and can also carry nucleic acids, but despite increased attention into their role in symbiotic interactions, they have not been shown to be broadly involved in host nutrition in animal-microbe interactions  (72). We imaged random tissue sections from five individuals using TEM and quantified the number of bacteria, bacteria with OMVs, and lysosomal structures in the bacteriocyte region. On average, of the 136 ± 35 Ca.
The TPM were sorted based on the average for the three replicates. For host transcriptomics, a de novo transcriptome assembly was generated from filtered mRNA reads using Trinity. After cleanup and deduplication, the final host transcriptome that consisted of 54,926 predicted genes was annotated with Trinotate. Protein Extraction and Proteomic Analyses. For 1D liquid chromatographytandem MS (LC-MS/MS) proteomics, tryptic digests from eight samples (four from one animal and four from three animals pooled) were separated using a 260-min gradient and roughly 110,000 MS/MS spectra were acquired per sample using the Orbitrap. The final protein identification database consisted of all protein sequences predicted from the Ca. R. santandreae genome and the database for common laboratory contaminants.
(38)th genes were of alphaproteobacterial origin and clustered with gene sequences of related Rhodospirillaceae (SI Appendix, Supplementary Note 2 and Figs. S8 and S9). Other Rhodospirillaceae such as Rhodospirillum rubrum only lacked a sedoheptulose-1,7-bisphosphatase but still encoded a canonical fructose-1,6-bisphosphatase for the last step in the CBB cycle that has the highest energy-saving potential (35) (Dataset S1A). This suggests that the most energy-efficient variant of PP i -dependent CBB cycle evolved independently in Ca. R. santandreae, possibly due to the same energy constraints that led to the selection of the most efficient sulfur oxidation pathway across the diversity of thiotrophic symbionts(38)(SI Appendix, Supplementary Note 2). The Ca. R. santandreae symbiont encoded form IA RuBisCO for carbon fixation rather than the form II RuBisCO that was previously identified by PCR amplification in another Ca.
ACKNOWLEDGMENTS. We acknowledge the  Hydra Institute team on Elba , especially  M. Weber ,  C. Lott ,  H. Kuhfuss , and  M. Schneider  for support during fieldwork. We thank  N. Dubilier ,  K. Altendorf , and  J. Ott  for project discussions and editorial advice on an early version of this manuscript. We thank  J. Wippler ,  A. Assié ,  C. P. Antony , and  T. Wagner  for project discussions. We acknowledge the  Max Planck Genome Centre Cologne  for library preparation and sequencing. We thank  N. Tebeka  and  S. Dyksma  for support with microautoradiography and  M. Sadowski  and  R. Yemanaberhan  for support during incubation experiments,  M. Jung  and  G. Sondej  for support during worm cultivations,  J. Kesting  and  A. Chan  for fieldwork help,  A. Gruhl  and  B. Geier  for support with microscopy,  E.
Puskás  for support in GC-MS measurements and  J. Zimmermann  for technical suggestions. This study was funded by the  Max Planck Society  through  N. Dubilier. M. K. was partially funded by the  North Carolina State University Chancellor's Faculty Excellence Program Cluster on Microbiomes and Complex Microbial Communities. H. R. G. -V. was partially funded by  Marie-Curie Intra -European Fellowship PIEF-GA-2011-301027 CARISYM.
Data (GFBio)  (78). The MS proteomics data and the protein sequence databases have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository  (79)  for the pure culture data with the dataset identifier PXD009856. The raw data for the EM-based quantitative image analysis have been deposited in Figshare (https://doi. org/10. 6084/m9. figshare. 7746806) (80). Code Availability. The script that was used to classify the transporter families is available at https://github. com/kbseah/tcdbparse_sqlite.
Expressed proteins detected in the proteome samples are indicated. Not all genes of certain pathways were transcribed, and not all transcribed genes were found in the proteomes (Dataset S1 B-E). Dotted arrows correspond to indirect synthesis of metabolites. Apr, sulfite reductase; bc 1 , cytochrome C oxidase type bc 1 ; Cyt. a 3 , cytochrome c oxidase type a 3 ; Cyt. C, cytochrome c; FccAB, flavocytochrome c sulfide dehydrogenase; Mce, mammalian cell entry proteins Mla; NDH, NADH-quinone oxidoreductase/dehydrogenase; PckG, phosphoenolpyruvate carboxykinase; PDH, pyruvate dehydrogenase complex; Pst, high-affinity phosphate transporter; Sat, ATP sulfurylase; SDH, succinate dehydrogenase; Sec, secretion pathway; Tat, twin-arginine translocation; TPP, trehalose-P phosphatase; TPS, trehalose-P-synthase; TST, thiosulfate sulfur transferase (rhodanese).
Such conditions can be solved using a symbolic computation software as Matlab Symbolic Toolbox. The procedure used to obtain triples from w 23 can be extended straightforwardly to a different moment vector as follows: • Define the moment vector w similarly as for w  23. The vector can be built by moment products of two different orders or more. For instance, products such as m 200 m 220 m 300 which combine moments of order 2, 3, and 4 can be also used. the vector w has to be built from moment products of the same nature and has to also include all of them. • Using Equation (  4 • Solve the following system:          L w 23 /ω x 0 0 L w 23 /ω y 0 I L w 23 /ω z -I 0. 0 0 L w 23 /ω z             α x α y α z    = 0, (16) where I and 0 are respectively the identity and zero matrices of the same size as L w 23 /ω x , L w 23 /ω y and L w 23 /ω z.
Validation Results In the following section, simulation results and real experiments are shown. For all the validation results, the spherical moments are computed directly using the pixel's grey levels without warping the images to the sphere space. The used formulas are given in References  [26, 27]  for the perspective and fisheye cases respectively: m ijk = Image x i s y j s z k s (ξ + z s ) 3 1 + ξz z I(x, y, t) dxdy, ( 20 ) where ξ is the distortion parameter and (x, y) are the coordinates of a point in the metric image. The formulas of x s , y s , and z s as functions of (x, y) can be found in Reference  [28]. Using Matlab with a computer equipped with a processor Intel(R) Core(TM) i5-7600 CPU @ 3. 50 GHz 3. 50 GHz and 16,0 Go RAM, the whole process including the computation of spherical moments of an image of size 480 × 640 pixels until the rotation estimation takes around 20 ms.
Real Experiments The following experimental results use the OVMIS (Omnidirectional Vision Dataset of the MIS laboratory) dataset (http://mis. u-picardie. fr/~g-caron/pub/data/OVMIS_dataset. zip). Based on the same database, the preliminary work  [23]  has provided several experimental results where the proposed method is compared to the SPHARM (SPherical HARmonic analyses) method  [15]  and to the phase correlation (COR) and photometric (PHO) methods  [29]. In the following, the proposed method is validated on a larger set of scenarios from the dataset. Moreover, we compare the performance of the proposed method using the spherical moments computed from the image intensities and from its gradient. We also test the effect of introducing the weighting function on the spherical moment computation of image acquired by catadioptric camera.
The used weighting is a function of the pixel coordinates (x, y) of the following form:  (21)  where r = (xu x ) 2 + (yu y ) 2 is the distance of the pixel to the principal point (u x , u y ) and σ is a scalar that tunes the wide of the image zone to be used. Note that W(x, y) has its maximum value 1 for r = r m. Figure  5a  shows the shape of the used weight function for this validation results. As can be seen from weighting function shape, the points close to the image border or to the blind zone in the mage center are given small weights to decrease the effect of appearance/disappearance of image parts. In all these experimental parts, the rotation motion is obtained by accumulating the estimated rotations between each two consecutive images. The first validation result shown in the video (Supplementary Materials) is based on Dataset 1 of OVMIS with the Staubli robot arm.
The considered sequence composed of 144 images has been acquired by applying regular pure rotations around the optical axis by a catadioptric camera mounted on the end effector of a Staubli in an indoor environment which corresponds to a rotation of 2. 5 • between two consecutive images. First, the proposed method is tested by considering all the image sequences. Then, one image from 10 and from 20 are considered, which corresponds to rotations of 25 • and 50 • , respectively, between tow consecutive images. As it can be seen from the video that the obtained results show that the proposed method estimates accurately the rotations in the three considered cases. W(x, y) = e -(r-rm ) 4 σ 4 The second validation result shown as well in the video (Supplementary Materials) is based on the Scenario 1 of the Pioneer database acquired using a catadioptric camera.
A similar setup to the previous case is used: a pure rotational motion around the z-axis in an indoor environment. The proposed method is tested by considering all the image sequences, one image from 10 and one from 20. The obtained results show again that the proposed method estimates accurately the rotations in the three considered cases. The last experiment tests the proposed method on the more challenging Scenario 3 of the OVMIS dataset of a pioneer robot moving according to the trajectory described in Figure  5b. The achieved path is of length 25. 27 m, in the form of 8 motions that include both rotational and translation motions. It has been achieved by the mobile robot in 160 s, which corresponds to 0. 187 m/s average speed. The ground truth is obtained by incorporating gyroscopic corrections into the odometry data based on wheel encoders.
However, the packing between the two protofilaments is different. Therefore, a-Syn fibrils exhibit assembly polymorphism as defined by  Riek (2017)  and described in Tau between paired helical filaments (PHFs) and straight filaments (SFs)  (Fitzpatrick et al. , 2017). In each protofilament of the new a-Syn polymorph 2a, successive rungs of ß-strands are related by helical symmetry with a rise of 4. 8 A ˚and a twist of À0. 80˚with the subunits within the two protofilaments packed in the same plane, facing each other (Figure  1D    For polymorph 2a (PDB ID 6SSX) and polymorph 2b (PDB ID 6SST), each a-Syn molecule within a protofilament is composed of eight in-register parallel ß-strands (ß0-7; Figure  1A,D  and E ): residues 16-20 (ß0),  38-44 (ß1), 46-50 (ß2), 52-56 (ß3), 61-66 (ß4), 68-72 (ß5), 76-79 (ß6), and 85-92 (ß7).
Conclusion We present here two new structures of a-Syn fibril polymorphs (polymorph 2a (PDB ID 6ssx), and polymorph 2b (PDB ID 6sst)). These differ in their protofilament interfaces but are formed by the same protofibril subunit structure, which is distinct from previously described a-Syn folds. Our results describe 3D structures very different from previous work and demonstrate how a-Syn amyloid fibrils can reach different cross-ß architectures in spite of having the same amino acid sequence. The structural information from the various a-Syn polymorphs allowed informed hypotheses on how amyloid fibrils may form and how their formation may be related to pathogenicity. More importantly, these structures add to the knowledge of the conformational space of this protein, which is central for structure-based design of imaging tracers or inhibitors of amyloid formation.
Electron microscopy Cryo-EM grids were prepared using a Leica EM GP automatic plunge freezer (Leica Microsystems) with 80% humidity at 20˚C. 3 mL aliquots were applied onto 60 s glow-discharged, 300 mesh, copper Quantifoil grids (R2/1). After blotting, grids were plunge frozen in liquid ethane cooled by liquid nitrogen. Micrographs were acquired on a Titan Krios (ThermoFisher Scientific) transmission electron microscope, operated at 300 kV and equipped with a Gatan Quantum-LS imaging energy filter (GIF, 20 eV zero loss energy window; Gatan Inc). Images were recorded on a K2 Summit electron counting direct detection camera (Gatan Inc) in dose fractionation mode (50 frames) using the Serial EM software  (Mastronarde, 2005)  at pixel sizes of 0. 831 A ˚or 0. 629 A ˚, and a total dose of ~69 electrons per square Angstrom (e -/A ˚2) for each micrograph.
Model building and refinement A model for the a-Syn polymorph 2a fibril was built into the RELION local resolution-filtered map with COOT  (Emsley and Cowtan, 2004) , by conserving as many secondary structure elements as possible from our previous a-Syn polymorph one model (PDB ID 6h6b)  (Guerrero-Ferreira et al. , 2018) , together with the use of secondary structure information derived from ssNMRs, which served as an initial model. The structure was then refined against the same map with PHENIX real space refine  (Afonine et al. , 2013)  using rotamer and Ramachandran restraints, and non-crystallographic symmetry and beta strand geometry constraints. The building and refinement of the a-Syn polymorph 2b model was more challenging due to the lower resolution of the map. An initial structure was built into the a-Syn polymorph 2b local resolution-filtered map by fitting of the a-Syn polymorph 2a model using COOT.
NMR spectroscopy NMR spectra were recorded at 20. 0 T static magnetic field using 3. 2 mm rotors and a triple-resonance probe. The reproducibility of the sample preparation was previously verified with 20 ms DARR fingerprint spectra  (Gath et al. , 2014a). The secondary chemical-shift analysis was based on the sequential assignments (BMRB accession code 18860) and was presented before  (Gath et al. , 2014a; Gath et al. , 2014b). The PAR spectrum  (De Pae ¨pe et al. , 2008; Lewandowski et al. , 2007)  was recorded using a mixing time of 8 ms. The assignments for the S87/A17-19 cross peaks are unambiguous within a range of 0. 15 ppm, corresponding to about ½ of the 13 C line width. Assignments of restraints given for reference on the full aliphatic region of the PAR spectrum in the.
Acknowledgements We thank  Liz Spycher ,  Jana Ebner ,  Alexandra Kronenberger ,  Daniel Schlatter ,  Daniela Huegin ,  Ralph Thoma ,  Christian Miscenic ,  Martin Siegrist ,  Sylwia Huber ,  Arne Rufer ,  Eric Kusznir ,  Peter Jakob ,  Tom Dunkley ,  Joerg Hoernschmeyer , and  Johannes Erny  at  Roche  for their technical support to clone, express, purify and characterize the different forms of a-Syn;  Kenneth N Goldie ,  Lubomir Kovacik  and  Ariane Fecteau-Lefebvre  for support in cryo-EM. Calculations were performed using the highperformance computing (HPC) infrastructure administered by the scientific computing center at the  University of Basel  (sciCORE; http://scicore. unibas. ch). The  Novo Nordisk Foundation Center for Protein Research  is supported financially by the  Novo Nordisk Foundation  ( NNF14CC0001 ).