dataesr/scientific-paragraphs-categorization huggingface dataset:
1) equipped with an infra-red filter and controlled by the uEyeCockpit software (iDS, https://www. ids-imaging. us/ids-software-suite. html). The first experiments were conducted in system water, and later in E3 medium. As we did not observe any significant change in locomotion of larvae in system water or E3 medium, nor across different days of experiment, we pooled the data acquired under these different conditions from different clutches. We referred to solutions devoid of drugs as "control solutions". To test the role of serotonin (5-HT) in the modulation of spontaneous swimming, the basal level of locomotion of each larva was first evaluated in control solution. After 10 minutes, larvae were transferred into a second swim arena with either control or homogenous 5-HT (250 µM) fresh solutions and a second measure was taken to compare within and between individuals.
4H-J ). For BAPTA, we pooled data from 3 days of experiment (1 performed in system water and 2 performed in E3 medium, Fig. 4H-J ). To test the role of lateral line hair cells in the behavioral response to environmental serotonin, we compared spontaneous swimming of larvae in control solution versus homogenous 5-HT. We pooled data from 4 days of experiment for CuSO4-treated larvae (2 performed in system water and 2 in E3 medium, Fig. 5A-B ), from 6 days of experiment for PLLablated larvae (all performed in E3 medium, Fig. 5D-E ) and from 3 days of experiment for OMP-ablated larvae (all performed in E3 medium, Fig. 5F-G ). The pH of all solutions was measured and buffered to be between 7,0 and 7,4. Simulation of the 5-HT gradient in the behavioral experiments. The concentration in the bath at any time is obtained from the numerical resolution of the unidimensional diffusion equation: 𝜕𝑐 𝜕𝑡 + 𝐷 𝜕 ! 𝑐 𝜕𝑥 ! = 0 where 𝐷 = 5.
4 • 10 "#$ m 2 /s is the diffusivity of serotonin in water  (52). The software Comsol (Finite Elements Methods) is used for the numerical simulations. A 1D mesh of 10000 elements discretizes a domain of length 𝐿 = 14 cm. The initial condition is taken as 𝑐(0) = 1. 46x10 "% mol/L for 𝑥 ∈ [6. 15 ; 7. 85] cm and 𝑐(0) = 0 mol/L for 𝑥 ∈ [0; 6. 15] cm and 𝑥 ∈ [7. 75; 14] cm. To estimate these quantities, we assumed that during the injection process, 200 µL of solution at 𝑐 = 5x10 "% mol/L were injected in a central region delimited by the comb of width of 1. 7 cm, accordingly changing the local concentration to 𝑐 = 1. 46x10 "% mol/L due to dilution. We here neglected the change in the level of the bath induced by this injection of this small volume. A noflux boundary condition is applied for 𝑥 = 0 and 𝑥 = 14 𝑐𝑚, which is expressed as 𝜕𝑐/𝜕𝑥 = 0 for both coordinates.
Acknowledgments: We wish to thank  Prof. Katie Kindt  for her generous gift of constructs and transgenic lines, as well as  Yannick Marie  and the ICM sequencing platform for their critical assistance in completing the transcriptomic analysis. We also thank  Prof. Judith Eisen  and  Prof. Karen Guillemin  for their generous support in completing some of the critical analysis as well as laser ablation experiments at  University of Oregon  with funding from the  Gordon and Betty Moore Foundation. French Ministry of Higher Education and Research doctoral fellowship (LD) Fondation pour la Recherche Médicale  ( FRM-FDT20170437143 ) (LD) and Team funding ( FRM-EQU202003010612 ) (CW)  Gordon and Betty Moore Foundation   Symbiosis Investigator  Award  GBMF9205  (https://doi. org/10. 37807/GBMF9205 ) ( Judith Eisen , funding LD)  Second Investissements d'Avenir program   LIGHT4DEAF   ANR-15-RHUS-0001  and  LabExLIFESENSES   ANR-10-LABX-65  ( NM )  LHW-376   Stiftung  (NM)  Fondation pour l'Audition FPA IDA03 (NM) Fondation Bettencourt-Schueller  ( FBS-don-0031 )  Research Grant  (CW)  U19 NIH Consortium  Grant # 1U19NS104653  (CW)  Foundation Schlumberger for Research & Education (FSER) (CW).
After 24 hours of recovery, behavior recordings were performed on 5 dpf larvae comparing control siblings and ablated larvae -note that all animals were exposed the same way to metronidazole. Statistics. Non-parametric Mann-Whitney tests were used for hypothesis testing and ran on Matlab using the 'ranksum' function. To test the effect of serotonin on percentage of time spent swimming, bout frequency and bout speed, we used linear mixed-effect models coded in R (https://github. com/wyartlab/Desban_Roussel_Neuromasts_2022) after excluding outliers according to Cook's distance greater than twice the amount of the cutoff value 4/n (for details about statistic methods and results, see Data S2). In all figures, * means that p < 0. 05, ** means that p < 0. 01, *** means that p < 0. 001 and **** means that p < 0.
Monoclonal Antibodies The immunogen for raising a monoclonal anti-Hwp1 was the peptide CDNPPQPDQPDDN (amino acids 154 to 166 of the protein encoded by GenBank sequence U64206). The peptide was synthesized and purified at the Protein Sciences laboratory of the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign. Methods for inoculation of mice, hybridoma formation, and enzyme-linked immunosorbent assay (ELISA) screening were published previously  (Coleman et al. , 2009)  and summarized here. Mice were immunized intraperitoneally with 0. 5 mg of the peptide emulsified in TiterMax for the first injection and 0. 25 mg of peptide in incomplete Freund's adjuvant for the final three injections. Injections were administered at a three-week interval. ELISAs were used to monitor mouse immune response, as well as to screen hybridoma subclones.
Wet mounts of immunolabeled cells were examined using an Olympus BX50 microscope equipped with the Olympus Fluoview FV1200 confocal system and Melles Griot Argon (488 nm) laser. An UP-PLAN 100X Oil objective with a Nomarski prism was used for all images that were captured with Olympus Fluoview software. A similar method was used to grow cells of different Candida species to assess immunolabeling with anti-Hwp1 MAb 2-E8. Growth in RPMI medium did not necessarily induce germ tube formation in other Candida species. Hwp1 production in C. dubliniensis CD36 was also assessed following growth in conditions demonstrated to increase HWP1 expression, specifically 10% serum in MilliQ water  (Caplice and Moran, 2015). A single colony from a YPD plate of strain CD36 was inoculated into 10 ml of YPD and incubated at 30°C for 18 h with 200 rpm shaking.
Bioinformatics Methods C. albicans sequences were downloaded from the Candida Genome Database (CGD; http://www. candidagenome. org; Skrzypek et al. , 2017). "A" alleles from the diploid genome assembly were used preferentially. Database searches used BLAST via the utility on either the CGD or NCBI website (https://blast. ncbi. nlm. nih. gov/ Blast. cgi). European Bioinformatics Institute (EMBL-EBI) tools were used for translating nucleotide sequences, sequence alignment, and other general processes (https://www. ebi. ac. uk/ services;  Cook et al. , 2017). SignalP-6. 0 Server (http://services. healthtech. dtu. dk/service. php?SignalP; Nielsen, 2017) was used to locate putative secretory signal peptides. The big-PI Fungal Predictor GPI Modification Site Prediction in Fungi was used to locate putative GPI addition sites (https://mendel.
DNA Sequence Correction Putative orthologs of C. albicans HWP1, RBT1, and HWP2 were identified from online databases as described above. The resulting sequences were examined for the presence of expected structural features such as a secretory signal peptide at the N-terminus of the predicted protein and a glycosylphosphatidylinositol (GPI) anchor addition site at the C-terminal end. Lack of such features suggested that the sequences may have errors that altered a predicted start site or caused a premature stop codon. Other sequences had unknown information (e. g. NNN) in the center of the coding region. To derive complete, accurate sequences for these genes, PCR primers were designed using the PrimerQuest Tool (https:// www. idtdna. com/pages/tools/primerquest) and synthesized by Integrated DNA Technologies (Coralville, IA).
Q5 High Fidelity DNA Polymerase (New England Biolabs) was used according to the manufacturer's instructions to amplify the problematic regions. PCR products were purified using the MultiScreen HTS 96-well Filtration System (Millipore). Sanger sequencing was completed at the Roy J. Carver Biotechnology Center DNA Services Lab (University of Illinois at Urbana-Champaign, Urbana, IL). Three sequences from C. orthopsilosis required correction: CORT_0E03570 (Supplementary File S1), CORT_0E03560 (Supplementary File S2), and CORT_0E05950 (Supplementary File S3). Complete experimental details and accession numbers for the corrected sequences are provided in the Supplementary Files.
A mixed model analysis of variance was used to assess the differences between treatments. Day, replicate (rep), treatment (trt), and mean number of germ tubes per BEC (gt) were considered in the analysis. Data were analyzed using PROC MIXED in SAS (SAS Institute, Cary, NC). Separation of means was performed with the LSMEANS option. Program commands included: data BEC; input day trt rep gt @@; proc mixed data = BEC; class day trt; model gt = trt; random day day*trt; lsmeans trt/pdiff.
albicans to BECs  (Staab and Sundstrom, 1998; Staab et al. , 1999). Sequence comparisons and alignments among the Hwp1/Rbt1/Hwp2 orthologs (Supplementary Table  S1 ) indicated that the Gln/Pro-rich sequences were unique to Hwp1 in C. albicans and C. dubliniensis although the C. dubliniensis Cd36_43360 sequence that best matched the peptide immunogen was imperfect (Table  2 ). The 13-mer immunogen peptide sequence was used as the query for a tblastn search of the genomes for species listed in Table  1. Additional partial sequence matches were revealed (Table  2 ) although the resulting proteins were unlikely to be present on the fungal cell surface. C. albicans Hwp1 was downloaded from the AlphaFold database of predicted protein structures (https://www. alphafold. ebi. ac. uk) to visualize the position of the 13-mer immunogen; AlphaFold Colab was used to predict a structure from the C.
dubliniensis Hwp1 sequence (Figure  4 ). AlphaFold predictions showed largely unstructured molecules although the predictions did not have a high level of confidence. However, both structures suggested surface-exposure of the immunogen. C. dubliniensis CD36, C. tropicalis MYA-3404, and C. parapsilosis CDC 317 were tested using the same growth conditions and immunolabeling methods that were successful for C. albicans; no anti-Hwp1 signals were observed (data not shown). Negative results for C. tropicalis and C. parapsilsosis were consistent with genomic information that suggested lack of an epitope that could be recognized by anti-Hwp1 MAb 2-E8 (Tables  1, 2 ; Supplementary Table  S1 ). The potential for a Hwp1 epitope to exist in C. dubliniensis (Table  2 ) prompted literature searches for alternative growth conditions that might produce sufficient Hwp1 protein for immunolabeling detection.
"A" alleles from the Candida Genome Database were used preferentially in the analysis. Gene names for other species similarly denote relative location and indicated that HWP1 and RBT1 were adjacent or near each other in species where both genes were found. The additional BLAST hits were not part of this gene cluster in any species. † The C. metapsilosis genome sequence used in CGOB was not identified in available resources. CGOB used "CMET" designations for gene names. C. metapsilosis BLAST analysis presented here used genome assembly GCA_008904905. 1, strain ATCC 96143  (Oh et al. , 2019). Gene designations shown above indicated the contig number (i. e. either contig 5 or 4 for the sequences included here) and the starting nucleotide number in the contig sequence. Supplementary Table  S1  shows gene names decoded into the CMET format for entries with available information.
albicans and C. dubliniensis. Hwp1 adhesive function would require sufficient Gln-Pro copies, as well as an overall protein length to display the region on the cell surface. It seems highly likely that anti-Hwp1 MAb 2-E8 should recognize all C. albicans and C. dubliniensis isolates. Immunofluorescence, immunogold electron microscopy, and AFM techniques used here support the idea that the Gln-Pro region is displayed prominently on the C. albicans cell surface (Figures  1 2 3 ). The AlphaFold algorithm uses deep multiple sequence alignments and information from Protein Database structure templates to arrive at structural predictions that have unprecedented accuracy  (Jumper et al. , 2021). The AlphaFold database (www. alphafold. ebi. ac. uk) includes the entire C. albicans proteome; the user-friendly AlphaFold Google Colab (see Materials and Methods) can predict structures from proteins yet to appear in the AlphaFold database.
cerevisiae SAG1 is syntenic with a C. dubliniensis ALS locus. Also, Sag1 and Als proteins appear to share a similar structure of the N-terminal domain that is responsible for adhesive (ligand-binding) function  (Oh et al. , 2021). In contrast, the idea that Hwp1 is an ortholog of S. cerevisiae a-agglutinin (Aga1) seems prompted by the observation that Hwp1 production and localization during C. albicans mating is specific to the a/a portion of the conjugation bridge  (Daniels et al. , 2003). Table  1  demonstrates that the HWP1 locus has a rather evolutionarily limited synteny pillar and database searching suggests that there does not appear to be a homolog of S. cerevisiae AGA1 in C. albicans. Alternatively, the nature of the interaction between Hwp1 and Als proteins may not involve ligand-binding but other mechanisms such as aggregation.
3J). Low signals on the yeast cell were consistent with fluorescence microscopy images that suggested abundant representation of Hwp1 only on the germ tube (Figure1). Genome database searching was used to predict the potential for the anti-Hwp1 MAb 2-E8 to recognize the surface of other fungal species that are closely related to C. albicans. C. albicans HWP1 (C4_03570W_A) is located on Chromosome 4 near two.
were downloaded from the AlphaFold Protein Structure Database (https://www. alphafold. ebi. ac. uk) or derived using AlphaFold Colab (AlphaFold v2. 1. 0; https://colab. research. google. com/github/deepmind/alphafold/blob/main/ notebooks/AlphaFold. ipynb). Structural visualization and alignments used the PyMOL Molecular Graphics System, Version 2. 5. 2 (Schrödinger, LLC).
ACKNOWLEDGMENTS We thank the staff of the  Roy J. Carver Biotechnology Center (CBC) Protein Sciences facility  for synthesis of the Hwp1 peptide. We thank the staff of the  CBC Immunological Resource Center  for producing the anti- Hwp1 MAb. Paula Sundstrom  ( Dartmouth University ) provided C. albicans strains  CAH7-1A1E2  and  CAHR3. William Fonzi  ( Georgetown University ) supplied C. albicans strain  CAI12. Derek Sullivan  ( Trinity University ) contributed C. dubliniensis  CD36.
Generate 3D-printed stages and adapt as needed Timing: days to weeks including design, printing, and testing 4. Special mouse holders for microscope stages were designed using specialized software. In this case we used TopSolid, a CAD/CAM (computer-aided design/computer-aided manufacturing) system. a. For each design, simulate 3D dimensions (including height, width, length, and orientation relative to the organ that each specific stage will help visualize). 5. Use 3D printer to generate the mouse holders. 6. Test mouse holders, preferably using a dummy mouse, to determine fit in the various microscope stages, and reach of the objectives.
ACKNOWLEDGMENTS This work was supported by  LT000047/2019-L  ( HFSP ) and  ALTF 1048-2016  (EMBO) to M. D. N. L. M. F. is an investigator CEEC of the Fundaca ˜o para a  Ciencia e a Tecnologia  ( CEECIND/03322/2018 ), and the laboratory is funded by  ERC  (FatTryp, ref. 771714 ). We are grateful to  Jose Rino ,  Sara Silva Pereira  ( iMM, Lisbon ), and  Daniel Costa  (attending veterinarian at  iMM rodent facility, Lisbon ) for their helpful input and comments for this manuscript. We thank  Brice Rotureau  ( Institut Pasteur, Paris ) for providing the triple reporter (TY1-TdTomato-FLuc) AnTat1. 1 E T. brucei parasite line used in this protocol, and  Fabien Guegan  ( iMM, Lisbon ) for generating the PAD1:GFP line used in this protocol. We acknowledge the  Rodent and Bioimaging  facilities of the  Instituto de Medicina Molecular.
Coffee Leaf Metabolomics-ESI-MS (-) Mode Three different species of C. anthonyi, C. arabica and C. canephora were also analyzed in ESI-MS (-) mode and the dataset included more than 4000 features. The PCA was performed and the score plot showed three clusters that were well separated. PC1 and PC2 explained 44% and 26%, respectively, of the total variation (Figure  1B ). Loading plots show the main discriminant metabolites found in each cluster (see Supplementary Materials Figure  S1. 1B). A detailed annotation of the metabolites previously investigated was carried out (see Supplementary Materials Table  S1 ). The three isomers of CQAs provided m/z 353. 0890, m/z 353. 0888 and m/z 353. 0887 as [M -H] -ions as expected and the three isomers of FQAs could also be identified (m/z included between 367.
Coffee Leaf Metabolomics-ESI-MS (-) Mode Three different species of C. anthonyi, C. arabica and C. canephora were also analyzed in ESI-MS (-) mode and the dataset included more than 4000 features. The PCA was performed and the score plot showed three clusters that were well separated. PC1 and PC2 explained 44% and 26%, respectively, of the total variation (Figure  1B ). Loading plots show the main discriminant metabolites found in each cluster (see Supplementary Materials Figure  S1B ). A detailed annotation of the metabolites previously investigated was carried out (see Supplementary Materials Table  S1 ). The three isomers of CQAs provided m/z 353. 0890, m/z 353. 0888 and m/z 353. 0887 as [M -H] -ions as expected and the three isomers of FQAs could also be identified (m/z included between 367.
Molecular Networks To confirm the annotation of the compounds detected in positive mode and to investigate further metabolites in the three coffee species, a molecular network (MN) was carried out on the coffee leaves dataset by setting a cosine score of 0. 5. Only the networks including at least two or more features linked to each other were analyzed. Figure  4A  shows a cluster including many m/z values corresponding to small molecules such as trigonelline. Trigonelline appears at m/z 138. 0553 (RT = 2. 39 min, δ = -2. 52 ppm) and the annotation was performed by comparing the spectrum of the target compound with the spectrum of the standard compound implemented in MetGem libraries. The CS associated with the spectrum of the standard compound was about 0. 61. Interestingly, this compound was mainly detected in the leaves of C.
87 ppm) and tryptophane at m/z 205. 0956 (RT = 6. 92 min, δ = 7. 61 ppm). While phenylalanine was mainly detected in the leaves of C. anthonyi and C. arabica, tryptophane was found to be predominant in the leaves of C. canephora. Figure  4B  shows a cluster with features corresponding to molecules with long alkyl chains. [29]. The node with m/z 437. 1068 (RT = 11. 10 min; δ = 2. 38 ppm) was linked to the node of mangiferin with a CS of 0. 97, suggesting that this M + H + ion could be attributed to homomangiferin; moreover, its m/z value was associated to that of the standard compound of the MetGem database with a CS = 0. 74. The fragments with m/z = 317. 0631 and 287. 0525 corresponding to the fragments at m/z = 303. 0497 and 273. 0389, previously found for mangiferin, were detected. The only difference was the presence of a methoxy on C5 of the xanthone unit to the previous fragments, which is missing in the chemical structure of mangiferin conferring a delta mass of 14 m/z (+CH 2 ).
0886 (RT = 12. 61 min), 519. 1541 (RT = 15. 46 min) and 589. 1920 (RT = 15. 19 min), showed the two peaks with m/z 303. 0497 and 273. 0389, previously found in the spectrum of mangiferin, suggesting that these molecules are structurally related to mangiferin. Figure  4D  showed a cluster where the three CQA isomers were strongly related to each other, with an upper CS value of 0. 90. The three features with m/z 355. 0997 (RT = 5. 70 min), 355. 1014 (RT = 7. 77 min), and 355. 1012 (RT = 9. 37 min) were attributed to 3-O-, 5-O-and 4-O-caffeoylquinic acid, respectively (δ = 7. 51, 2. 71 and 3. 27 ppm). Moreover, a node with an m/z of 369. 1175 (RT = 10. 78 min) was identified and its spectrum matched that of feruloylquinic acid proposed by the MetGem database (CS = 0. 96, δ = 1. 38 ppm). Two other CQA derivatives related to the three main CQA isomers were found.
94). The main matching fragment was found at m/z = 153. 0176, which corresponds to the fragment C 7 H 4 O 4 formed after the classical breaking of the ring C of flavanone  [32]. Other fragments at m/z = 215. 0703, 149. 0171, and 107. 0442 were also specific to this compound. The node corresponding to this mass was tightly linked to a node with m/z = 451. 1229 (C 21 H 22 O 11 , RT = 9. 40), which was attributed to a 3-O-glucoside dihydrokaempferol (δ = 1. 31 ppm). Among the matching fragments, the m/z = 153. 0126 was found after the neutral loss of the sugar (m/z = 289. 0695; C 21 H 22 O 11 -C 6 H 12 O 6 ). Two features among the compounds mainly found in C. anthonyi leaves were related to a benzophenone structure according to the analog database. The ion with m/z 247. 0593 (RT = 6. 71 min) was associated with the structure of the iriflophenone (C 13 H 10 O 5 ) nonglycosylated with the addition of a hydroxyl group (δ = 3.
Data Processing ProteoWizard MSConvert tools (Version 3. 03. 9393, 64-bit) were used to convert raw data (. d Agilent ones) to. mzXML file. Peak Picking was chosen as a filter option. All data preprocessing and data processing were performed on the Workflow4Metabolomics infrastructure (https://workflow4metabolomics. org) (accessed on 15 April 2022). Detailed steps and parameters that were used for data processing are publicly available on the W4M workflow repository (https://usegalaxy. fr/u/amontis/h/coffee-published-2022) (accessed on 15 April 2022). Data preprocessing is based on XCMS software which allows performing the extraction of ions, their alignment across the samples, peak grouping, the retention time correction and annotation of isotope peaks, adducts and fragments. Matched Filter algorithms  [37]  were used with the parameters adapted for an Agilent 6520 series LC-QTOF.
10) from Agilent. Standard samples were also injected with the same LC conditions to confirm the identity of the most significant metabolites. In addition, data-dependent MS/MS acquisition was performed, and the acquired data were used to build a molecular network in order to have a global display of all related molecules. Data preprocessing for molecular networks were performed with MZmine 2 (version 2. 53) (https://mzmine. github. io) (accessed on 20 April 2022) followed by MetGem 1. 3. 4 (https://metgem. github. io/) (accessed on 21 April 2022) software. The main databases used for the preliminary annotation step were PubChem and SciFinder ® online platforms. The main databases used for the annotation of the displayed molecules of molecular networks were GNPS library, PhytoChemical, Pesticides, NIH Natural Products, EMBL Metabolomics Core Facility, GNPS Collection Miscellaneous, GNPS Sigma's Mass Spectrometry Metabolite and MIADP Spectral libraries.