dataesr/scientific-paragraphs-categorization huggingface dataset:
MASS SPECTROMETRY ANALYSIS The spots of interest were excised from the gels, destained and digested by Trypsin Gold Mass Spectrometry grade (Promega) overnight at 37°C as previously described  (26). Protein identification was performed either by MALDI-TOF MS or by Nano-LC-ESI-MS/MS. MALDI-TOF MS analysis was performed on an Applied Biosystem, Voyager DE Pro MALDI-TOF. The instrument was used in reflector mode, measuring peptide masses on a range of 500-4,000 Da. Calibration points were based on the masses of the matrix cluster or trypsin autolysis products (m/z 842, m/z 2211). Protein identification was performed by comparison of measured peptide masses with the theoretical mass fingerprint of porcine OBP (GenBank accession number NP_998961), VEG (S77587), and SAL (P81608) 1 obtained with the following parameters: trypsin digestion with two missed cleavages allowed, cysteines in reduced form, acrylamide adducts, methionine oxidized (MSO), and monoisotopic peptide masses as [M + H] +.
Nano-LC-ESI-MS/MS was carried on a hybrid quadrupole time-of-flight mass spectrometer (Q-Star, Applied Biosystems) equipped with a nanoelectrospray ion source coupled with a nano HPLC system (LC Packings Dionex). Database searching was performed using Mascot software (MS/MS ion search module) in the NCBInr database. Search parameters were as follow: other mammalians as taxonomy, 50 ppm tolerance for the parent ion mass and 50 amu for the MS/MS fragment ions, one missed cleavage allowed, carbamidomethylation of cysteine and methionine oxidation as possible modifications. Only candidate proteins with a significant Mascot score were taken into consideration (significance threshold for candidate <0. 05 using MudPIT scoring method and an expectation value for ion peptides <0. 05).
AMPLIFICATION AND MOLECULAR CLONING OF SUS SCROFA EOGT Messenger RNA obtained by total RNA extraction (see above) were reverse transcribed into cDNA with the Sensiscript III RT kit (Invitrogen) using a 3 -end gene specific primer (5 -TCACTGGGATCCCCGAGCTCATCATGTTTGTTCTT-3 ) designed from the transcript ID ENSSSCT00000012589 (Ensembl database, Sus scrofa genome). PCR amplification of EOGT in each tissue was carried out on a thermal cycler (Bio-Rad) with 1 µl of RT product as template with Platinum® Taq DNA polymerase High Fidelity (Invitrogen), with primers (Sense 5 -ATGTTAATGTTGCTTGTCTTTGGAGCATTGCTT-3 and antisense 5 -TTAGAGCTCATCATGTTTGTTCTTAAAAGGCCACTT-3 ), according to manufacturer's instructions. Touchdown PCR was performed as described above. The single product obtained by amplification from adult male RM was cloned into pCR® 4-TOPO vector (Invitrogen).
SEQUENCE ANALYSIS AND PHYLOGENETIC RECONSTRUCTION Sequences were retrieved by BLASTp searches of the NCBI non-redundant database using S. scrofa EOGT protein sequence (ENSSSCP00000012260) and S. scrofa OGT protein sequence (ENSSSCP00000013198) as a query (Data 1 in Supplementary Material). Only sequences that aligned the entire length with an e-value not higher than 10 -6 were kept for multiple sequence alignment in order to keep as much informative sites as possible for phylogenetic reconstruction. Sequences of a same species that were 100% identical to one another or entirely included in a longer one were eliminated to remove redundancy. We performed phylogenetic analyses using two different approaches, Bayesian estimation and bootstrapped maximum likelihood (ML). The phylogenic reconstruction was performed with 48 sequences from model insect species (Drosophila melanogaster, Bombyx mori, Anopheles gambiae, Aedes aegypti, and Apis mellifera) as well as from other models or agronomical species (Mus musculus, Rattus norvegicus, Danio rerio, Tetraodon nigroviridis, Takifugu rubripes, Xenopus laevis, Xenopus tropicalis, Bos taurus, Equus caballus, Sus scrofa, Gallus gallus, and Homo sapiens).
Sequences were aligned using MUSCLE  (30)  with default parameters and the multiple sequence alignment was manually examined using JALVIEW  (31, 32)  (Data 2 in Supplementary Material). We performed phylogenetic analyses using ML estimation with the RAxML software  (33). We systematically ran 100 bootstrap replicates followed by a ML search for the best-scoring tree. We chose WAG model of amino acids evolution because it returned the best posterior probability score in the corresponding Bayesian phylogenetic analysis (data not shown) done using MRBAYES software  (34). We used a model with four categories of estimated gamma rates of evolution as well as an estimate of the proportion of invariable sites. The tree was generated using MEGA 5  (35)  and is presented with bootstrap values. Each protein was also assessed for targeting to the extracellular space using two different prediction methods: WoLF PSORT (36) and SignalP 4.
SEARCH FOR OBP AND VEG SPLICING VARIANTS BY RACE-PCR AND "IN SILICO" ANALYSIS Interestingly, the sequence of the identified OBP and VEG isoforms with apparent MW of around 15 kDa always lacks the N-terminus (Table  3 ). VEG isoforms of lower MW were already observed in human tears [four isoforms of 14-16 kDa in Ref. (41, 42) ]. The origin of N-terminal heterogeneity of VEG has been debated and led authors to speculate involvement of genetic polymorphism. The structure of porcine VEG encoding gene (called LCN1, GenBank #U96150) is known  (43) , but not its regulation. So, we have first hypothesized that this short OBP and VEG isoforms could come from alternative splicing of their coding gene. Amplification of potential transcripts of different sizes was undertaken several times and on different animals by RACE-PCR.
We obtained each time a single transcript of full-length sequence for VEG (data not shown). This is consistent with expression studies of human VEG/LCN1 gene, that showed a single size of RT-PCR products obtained with specific primers in not only olfactory tissue, but also in lachrymal gland, placenta, and mammary gland  (19). The search for short variants of OBP by RACE-PCR was also unsuccessful and we obtained a single-size PCR product around 500 bp (data not shown). Since these results, the pig genome has been sequenced and made available at Ensembl database. We have thus performed blast analysis to search for putative splicing variants for OBP, VEG, and SAL. The SAL1 gene (Ensembl: ENSSSCG00000005474) has only one transcript (ENSSSCT00000006020) corresponding to the coding of the full-length (mature) protein of 175 amino acids.
MOLECULAR CLONING OF SUS SCROFA EOGT cDNA AND PHYLOGENETIC ANALYSIS The report of a new OGT in Drosophila, linking a single O-GlcNAc moiety on Ser and Thr residues of secreted proteins (28) supported our findings on OBP O-GlcNAcylation. The availability of pig genome sequence gave us the opportunity to identify and clone the EOGT cDNA from pig olfactory tissues. We have blasted the pig genome (Ensembl database) with D. melanogaster EOGT sequence and designed primers from the 3 and 5 ends of the transcript ID ENSSSCT00000012589. A single PCR product was obtained in all tissues of RM and VNO from pre-pubertal and pubertal males and females (Figure  5 ), but not in the controls (PCR mix without DNA template or without DNA polymerase). The PCR product from male RM was cloned and sequenced. The cDNA sequence is 1696 bp long, and starts with the ATG codon for initiating the translation and a predicted signal peptide of 18 amino acids [SignalP,  (37) ], leading after cleavage to a mature protein of 509 amino acids.
The EOGT sequence obtained from pig tissue was 100% identical to the unique transcript ID ENSSSCT00000012589 reported in Ensembl database (pig genome). The full-length cDNA sequence of S. scrofa EOGT was deposited in GenBank database under accession number JX546149. S. scrofa EOGT is 48. 9% identical to D. melanogaster EOGT. To confirm the cloning of an EOGT in S. scrofa we performed a phylogenetic analysis. Glycosyl transferases (EC 2. sequences. Most of the sequences clustered in the EOGT branch are predicted as targeted to the extracellular space, which is in agreement with the function of the EOGT described by Sakaidani et al. (28).
IS SUS SCROFA EOGT RESPONSIBLE FOR O-GLcNAcylation OF OBP ISOFORMS? We have cloned and sequenced the cDNA encoding EOGT in Sus scrofa from tissues coming from RM and VNO in animals of different age and sex. Thus, it seems that EOGT is expressed whatever the physiological status of pigs. In addition, the phylogenetic analysis confirmed that our corresponding Sus scrofa protein clustered with the characterized DmEOGT (28) as well as with mammalian EOGT orthologs. They belong to a specific EOGT phylogenic subgroup where the majority of proteins are predicted as targeted to the extracellular space. This EOGT sub-group clearly segregates from the two other sub-groups AGO61 and OGT. AGO61 is a putative GT from the same family as EOGT in the CAZy database  (60). One Sus scrofa gene is found in each of these sub-groups but the Sus scrofa gene described in this paper is the ortholog of DmEOGT.
More experiments are required to demonstrate the role of Sus scrofa EOGT. The EOGT could be expressed in the yeast, since no similar sequence to those of EOGT has been found yet in the databases. Thus, the EOGT purified from the yeast would come only from overexpression of the porcine form. We have already overexpressed the porcine OBP in Pichia pastoris with very good yields  (26)  and the linking of O-GlcNAc on recombinant OBP by recombinant EOGT could easily be monitored with UDP-GlcNAc as substrate. Alternatively, expression of OBP in mammalian cell lines deficient in EOGT would be useful.
ACKNOWLEDGMENTS The authors thank  INRA  and  CNRS  for funding. Patricia Nagnan-Le Meillour  and  Anne-Sophie Vercoutter-Edouart  thank  Marlène Mortuaire  for technical contribution. Patricia Nagnan-Le Meillour  is grateful to  Dr. Pelosi  for the kind gift of anti-VEG and anti-SAL antibodies. We also thank the two reviewers who made interesting remarks and helped to improve the manuscript.
ACKNOWLEDGEMENTS Part of the work from our laboratory reviewed here was supported by grant #  PICT08-639  from the  National Agency for the Promotion of Science and Technology  and grant  PIP2378  from the  Argentine Research Council (CONICET)  to RGG and  GMC. The authors are grateful to  Ms. Yolanda Sosa  for editorial assistance. PCR and RGG are CONICET career researchers; GMC is CIC-PBA career researcher. None of the authors has conflicts of interest concerning this manuscript.
ACKNOWLEDGMENTS We would like to acknowledge support from the  National Institute for Agricultural Research (INRA) ; the  National Center for Scientific Research (CNRS) ; the  Burgundy Regional council ; the  EU European Regional Development Fund (FEDER) ; the  French National Research Agency (ANR ; in particular the  JC/JC ANR MEMOLAP program ); The  University of Burgundy  (uB); The  European Chemoreception Research Organization (ECRO) ;  The Association for Chemoreception Sciences (AChemS) ; and The  French Ministry of Higher Education and Research (MESR).
Acknowledgements This work was supported by the  Agence Nationale de la Recherche (ANR)  through the  LabEx  project  CSC  and the  International Center for Frontier Research in Chemistry (icFRC). ANR funding to A. T. and J. H through the grant PentaGate is gratefully acknowledged. J. P. C. is grateful to the  Kavli Institute for Brain & Mind University of California San Diego.
Gene array profiling For gene array profiling DRG were grown at the same conditions as for the growth cone collapse assay. RNA was extracted from DRG explants growing 24 hours in control conditions or in conditions with 100 ng/mL Sema3A using RNA extraction kit (Qiagen, RNeasy mini kit). Quantity and quality of RNA were determined by spectrometry (Thermo Scientific, Nanodrop) and by electrophoresis in 2% agarose gel. Gene array profiling was performed by IGBMC (Strasbourg) using Affimetrix platform. After data processing at IGBMC, it was assumed that gene expression of a specific gene was present if the signal strength for that gene was higher than 4.
Intracellular Ca 2+ imaging Intracellular [Ca 2+ ] i recordings were performed on DRG neurons loaded with 10 mM Fura-2 AM-0. 04% Pluronic 127 for 30 min in humidified 5% CO 2 incubator at 37uC, washed twice in HBSS and incubated for 30 more min. The cells were then transferred to an inverted epifluorescence microscope (Axiovert, Zeiss, Germany) equipped with an UPlanFL 40/0. 75 objective. The cells were alternatively illuminated at 340 nm and 380 nm and image pairs of the 520 nm light emission were recorded every 2 s for 30 min. Recordings were followed using MetaFluor Fluorescence Ratio Imaging software. The ratio of fluorescence intensities (Ex340 nm/Ex380 nm) was calculated on a pixel basis for each image pair. Increase in relative Fura-2 340/380 fluorescence indicates increase in free intracellular calcium  [34, 35].
Semaphorin 3A induces intracellular Ca 2+ elevation Intracellular free Ca 2+ concentration was measured using the Fura-2 fluorescent probe. In initial experiments we have evaluated growth cone response to 60 mM KCl depolarization, which was used as positive control to check whether change of intracellular Ca 2+ concentration can be observed at chosen regions of interest (ROI). As 100% of analyzed ROI were sensitive to 60 mM KCl (data not shown), which opens all neuronal VGCC due to electroosmosis, we concluded that this method of Ca 2+ imaging is suitable to study whether Sema3A response is a Ca 2+ dependent process. The Fura-2 signal was recorded at least for 300 s to establish the baseline followed by at least 300 s recording after addition of Sema3A. DRG treatment with 100 ng/mL of Sema3A resulted in slight but significant and steady 13% intracellular Ca 2+ elevation.
Whatever the training procedure, 24 h after the last conditioning session, freezing to the context was assessed by again placing each mouse in the conditioning chamber. The level of freezing was measured during 4 min, no tone or foot-shock being presented to the animal. Two hours later, mice were tested for freezing to the tone in the modified context. Two minutes after introduction in the modified chamber, freezing was recorded during a 2-min tone presentation. Freezing is defined as the lack of movement besides breathing according to  Blanchard and Blanchard (1969). This behavior was both automatically recorded and blind scored by an experimenter every 5 sec during conditioning and recall test sessions. Data were converted to the percentage of samples scored at freezing and calculated for the 4-min context recall test, the 2-min pre-tone, and the 2-min tone tests.
Molecular Dynamics System Setup CG-MD simulations were performed to investigate the homo and hetero association of NRP1 and PLXA1 TM domains using the GROMACS software package (version 4. 5. 4) [71, 72]. The TM peptides, the lipids and the water CG particles were described with the MARTINI force-field version 2. 1  [49, 50]  extensively used for the study of various peptide-lipid membrane systems  [54]. Images were created using the VMD software  [73]  (http://www. ks. uiuc. edu/Research/vmd/).
TM Peptide Sequences The two TM sequences used in the simulations correspond to the native potential sequences as found in the Uniprot database (http://www. uniprot. org/) (Table  1 ). We adjusted the length of the TM domains by adding a few residues on each side, in order to design a 28 amino acid sequence. For the sake of clarity, the TM sequences have been re-numbered 1 to 28 throughout this paper. The TM domain of NRP1 is characterized by two successive GxxxG motifs G 16 xxxG 20 xxxG 24. The PLXA1 TM sequence is characterized by the presence of 6 Gly residues, 5 being consecutive in the sequence constituting the G 11 GGGG 15 motif. Another GxxxG like motif, G 9 IGGG 13 , is observed overlapping the previous one. Considering the a helical structure of the TM domains, the 6 Gly residues of the PLXA1 TM domain are distributed over all the helix faces, covering almost two helix turns, while the 3 Gly residues in the NRP1 TM domain are aligned on only one helix face.
System Analysis Tools provided in the Gromacs package were used for the analyses. The associated state of the dimer was defined from the analysis of inter-helix distance (distance between the center of mass of the helix backbones, COM) and of inter-helix contact distance (minimal distance between the helix backbones). The two helices were considered associated when the closest contact distance was less than 0. 5 nm. The RMSD (Root Mean Square Deviation) matrix, which compares all the conformations generated during the simulation, was calculated to identify the periods of the simulation during which the dimer structure is stabilized. A dimer is stable when the RMSD value (calculated over the backbone beads) is less than 0. 3 nm. The longest period of the dimer stabilization was chosen to calculate the contact matrix that represents the smallest distances between the backbone beads of the residue pairs, on average.
TM domain sequences of human Neuropilin-1 (NRP1) and Plexin-A1 (PLXA1), protein names, identifiers, entry names taken from the Uniprot database (http://www. uniprot. org/)and TM domain sequences used in CG-MD simulations. For the sake of clarity, the TM sequences have been re-numbered 1 to 28 throughout this paper. doi:10. 1371/journal. pone. 0097779. t001.
Mass Spectrometry All experiments were acquired using a QExactive mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA), equipped with a nanospray ionization source (Thermo Fisher). Nanospray was achieved using a coated fused silica emitter (New Objective, Woburn, MA, USA) (360 mm o. d. /50 mm i. d. ; 730 mm tip i. d. ) held at 1. 5 kV. The ion transfer capillary was held at 220 ˚C. Full mass spectra were recorded in positive ion mode over a 400-1600 m/z range and with a resolution setting of 70000 FWHM (@ m/z 200) with 1 microscan per second. Each full scan was followed by 7 MS/MS events, acquired at a resolution of 17,500 FWHM, sequentially generated in a data dependent manner on the top seven most abundant isotope patterns with charge §2, selected with an isolation window of 2 m/z for the survey scan, fragmented by higher energy collisional dissociation (HCD) with normalized collision energies of 30 and dynamically excluded for 30 s.
Data Analysis All data generated were searched using the Sequest search engine contained in the Thermo Scientific Proteome Discoverer software, version 1. 4. The experimental MS/MS spectra were correlated to tryptic peptide sequences by comparison with the theoretical mass spectra obtained by in silico digestion of the human protein database (about 228763 entries), downloaded January 2013 from the National Centre for Biotechnology Information (NCBI) website (www. ncbi. nlm. nih. gov). The following criteria were used for the identification of peptide sequences and related proteins: trypsin as enzyme; three missed cleavages per peptide were allowed and mass tolerances of ¡50 ppm for precursor ions and ¡0. 8 Da for fragment ions were used. Validation based on separate target and decoy searches and subsequent calculation of classical score-based false discovery rates (FDR) were used for assessing the statistical significance of the identifications.
Identification of proteins in spots 1-13 The poor matching of spots 1-13 in Figure  2  with those of maps indicated above forced us to assign their identity by LC-MS/MS. Spots were carefully excised from the gel; destained; digested with trypsin and peptide mixtures submitted to nanoLC-MS/MS following the procedure detailed in the experimental section. After searching the MS fragmentation data against the databases indicated, a confident identification was obtained for all of the queried proteins. Unambiguous identification was achieved also in cases in which spot of interest (i. e. spot 6) contained small amounts of interfering components which comigrated with major protein. For each protein identified, detailed identification data, including protein and gene names, accession number, uniprot ID, pI and molecular mass (theoretical); sequest score; spectral count and unique peptides identified; are shown in Table  2.
Given the difficulty to investigate the resulting network (not shown), due to the high number of genes inserted in the database, a number of genes that showed no/poor interactions were taken off from the pathway. As shown in Figure  S3 , the other genes that showed interactions with the osteoclast pathway genes, TREM-2 and DAP12, were maintained and integrated in the system. In particular, the proteins found in our study that seemed to participate in the system were: EEF1D, GAPDH, PGK1, HSPA4, AKR1A1, HNRNPH1, CCT5 and CCT3 (evidenced by a red-dotted line panel). With the aim to validate these results, the STRING (Search Tool for the Retrieval of Interacting Genes, http://string-db. org) database was applied indicating as query entry the 12 genes found to be involved in the osteoclast pathway plus TREM2 and DAP12 genes and the list of genes encoding the 21 altered proteins of this study (Figure  S4 ).
This database not only confirmed the data found with GeneMANIA but also added some new interactions to the system. As it can be seen in Figure  S4 , some new genes (in the red dotted-line circle) including PGAM1, VDAC2, ALDOA, ENO1 and PDXP resulted to be also well integrated in the osteoclast pathway. In particular 12 proteins (EEF1D, GAPDH, HSPA4, CCT3, CCT5, ENO1, PDXP, HNRNPH1, ALDOA, PGAM1, VDAC2 and PGK1), among the 21 proteins identified with the proteomic analysis, seem to be in relation with the osteoclast pathway. Even more interesting is the finding that about one half of these proteins (GAPDH, PGK1, PGAM1, ALDOA, ENO1) is involved in the glycolytic processes. Thus, a correlation between the genes involved in glycolysis and the genes involved in the osteoclast pathway does exist.
Second, lymphoblastoid B-cells provide continually sufficient biomaterial for proteomic analyses, which is not possible from direct specimen sampling of patients. The fact that re-sampling patients will not be required, while avoiding unnecessary discomfort to the patient, allays concerns of unavailable re-sampling because of patient geographical location, death or other factors. Third, the presence in the literature of a proteome map and a database of lymphoblastoid cells, generated by characterizing protein spots on 2-DE  (26, 27) , allowed to identify a number of spots by gel-matching. Thus, despite some inherent limitations, lymphoblastoid cell lines are increasingly recognized an important resource for genetic and functional research of neurological disorders. Nevertheless, in a very recent paper, Ohgidani et al.
Acknowledgments The authors are deeply grateful to  Laura Fossati Onlus  ( Montesegale, Pavia, Italy ) for the generous financial support provided to the  Biochemistry Unit of the Department of Molecular Medicine  for the realization of this work. Our thanks also go to  Dr. Silvia Bione  ( National Research Council, Pavia ) and  Dr. Viola Baiutti  ( Department of Biology and Biotechnologies, University of Pavia ) for generating bioinformatic data. Dr. Anna Maria Floriano  ( Department of Molecular Medicine ) is finally acknowledged for her excellent technical assistance with 2D-electrophoretic runs.
This study was supported by the  Italian Ministry of University and Research  for the  PON  project ( 01_01426 , AMA, PM) and by  CARE-G project  financed by  Regione Lombardia  (ADP, PM). The authors are deeply grateful to  Laura Fossati Onlus  ( Montesegale, Pavia, Italy ) for the generous financial support provided to the  Biochemistry Unit of the Department of Molecular Medicine  for the realization of this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.