dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS MALDI-TOF MS analyses were performed on the Toulouse Proteomics platform (http://proteomique. ipbs. fr/). Microscopy analyses were performed on the Toulouse Imaging platform (http://trigenotoul. com). The authors also wish to thank  Dr. Cécile Albenne  and  Carole Pichereaux  for help in MALDI-TOF MS analyses and  Dr. Laurent Deslandes  for the gift of the two pAM-PAT derived binary vectors. They are also grateful to  Olivier Catrice ,  Josiane Chourré , and  David Roujol  for technical support. Lipid analyses were performed at the  Functional Genomic Center of Bordeaux -Metabolome/Lipidome platform , which is supported by the  MetaboHUB - ANR-11-INBS-0010  grant (http: //metabolome. cgfb. u-bordeaux. fr/).
Isolation of Ueq 12-1 Specimens of the sea anemone U. eques were collected off the coast of Tromsø, Norway, and ectoderm secretions/mucus were obtained by electrical stimulation. The released exudate containing peptides and other hydrophobic components was desalted and concentrated using solid phase extraction (SPE). The antibacterial effect of the extract was observed against the Gram-positive strain Corynebacterium glutamicum at concentrations as low as 80 µg/mL. The same extract displayed an inhibiting effect on the TRPA1 ion channel at 0. 1 mg/mL but did not affect the TRPV1 and TRPV3 channels in the Fluo-4-based intracellular calcium assay (data not shown). In order to identify fractions with bioactive components, the extract was fractionated by preparative RP-HPLC (Figure  1 ). All the obtained fractions were subsequently tested for both antibacterial and TRPA1 activities.
The fraction eluting after 27 min displayed antibacterial activity against C. glutamicum. In the Ca 2+ influx assay, the same fraction was found to potentiate the TRPA1 ion channel (data not shown). The crude extract displayed a net inhibition of TRPA1, which is the opposite effect observed for the HPLC fraction: this is probably because of the presence of other interfering bioactive compounds. The bioactive fraction was shown to consist of a peptide with a monoisotopic molecular mass of 4788. 63 Da, as measured by HR-ESI-MS. Toxins 2017, 9, 154 3 of 24 opposite effect observed for the HPLC fraction: this is probably because of the presence of other interfering bioactive compounds. The bioactive fraction was shown to consist of a peptide with a monoisotopic molecular mass of 4788. 63 Da, as measured by HR-ESI-MS.
The recombinant Ueq 12-1 had the same retention time as the native peptide when fractionated by reverse-phase HPLC (data not shown), producing the same effect in electrophysiological tests on TRPA1 and in behavioral tests in mice. This implies that they were identical. Moreover, analysis of 1H NMR spectra revealed the complete identity of natural and recombinant Ueq12-1 samples at pH 3. 0. The total yield of Ueq 12-1 was approximately 0. 7 mg per liter of bacterial culture. The average molecular mass of the recombinant product, determined by MALDI mass spectrometry (4792. 60 Da), was in accordance with the theoretical mass calculated from the sequence data (4792. 13 Da), and the average mass of the native peptide measured by HR ESI mass spectrometry (4792. 45 Da).
Spatial Structure of Ueq 12-1 in Water Solution In order to determine the fold of Ueq 12-1, the structure of the protein was resolved in water solution by NMR spectroscopy. A set of 20 possible structures was calculated using the CYANA program  [29]  from 100 random starting points using the following experimental data: upper and lower NOE-based distance restraints, torsion angle restraints, and hydrogen bonds restraints (Figure  3 ). The statistics of the obtained set of Ueq 12-1 structures are shown in Table  1.
Spatial Structure of Ueq 12-1 in Water Solution In order to determine the fold of Ueq 12-1, the structure of the protein was resolved in water solution by NMR spectroscopy. A set of 20 possible structures was calculated using the CYANA program  [29]  from 100 random starting points using the following experimental data: upper and lower NOE-based distance restraints, torsion angle restraints, and hydrogen bonds restraints (Figure  3 ). The statistics of the obtained set of Ueq 12-1 structures are shown in Table  1. The set of structures is characterized by a relatively low CYANA target function and residual restraint violations, and a low RMSD value for backbone atoms, suggesting that the structure of Ueq 12-1 is well-converged and defined accurately by the experimental data. The set of structures is characterized by a relatively low CYANA target function and residual restraint violations, and a low RMSD value for backbone atoms, suggesting that the structure of Ueq 12-1 is well-converged and defined accurately by the experimental data.
Primary Structure Analysis of Ueq 12-1 Ueq 12-1 is a 45-amino acid anionic peptide containing 10 cysteines engaged in five intramolecular disulfide bonds. No significantly homologous peptides were found in the databases. Based on earlier results, sea anemones may be considered leaders among the venomous animals in terms of the structural variety of polypeptides in their venoms and mucus. Polypeptides from the animal venom usually contain an even number of cysteine residues normally involved in the formation of disulfide bonds forming a rigid structure, more resistant to proteolysis  [17, 33]. Ueq 12-1 displays no sequence homology to known characterized sea anemone neurotoxins. The majority of characterized cysteine-rich peptides from sea anemones consist of 25-60 amino acid residues, 4-10 cysteine residues and a considerable number of positively charged residues (Lys, Arg) forming positively charged clusters on the surface  [1, 34].
The given full name is τ-AnmTx Ueq 12-1 (short name Ueq 12-1). This means that the peptide is the first representative of a 12th subgroup according to the classification proposed by Mikov  [32]. No highly homologous peptides or gene products were found using the NCBI BLAST search engine in non-redundant protein sequences (nr) database and Transcriptome shotgun assembly proteins (Tsa_nr) database or within searchable antimicrobial peptide databases. Even the StellaBase (the Nematostella vectensis genomics database), Pocillopora Transcriptomics Database (Pocillopora damicornis, cauliflower coral) and EdwardsiellaBase (the Edwardsiella lineata Genomic Database) returned no homologous sequences. Furthermore, no conservative protein domains were detected using the InterProScan tool. We found some similarities in the cysteine distribution pattern with small cysteine-rich peptides (SCRiPs) from corals and sea anemones extracted from EST databases  [35].
Additionally, one cDNA coding for SCRiP peptide (TSA: Anthopleura elegantissima comp63456_c0_seq1 transcribed RNA sequence, GBYC01024820. 1) similar to Ueq 12-1 was found in Transcriptome shotgun assembly (TSA) database using TBLASTN search. We should note that a variety of different cDNAs coding for SCRiPs peptides could be identified in the TSA database using known SCRiPs as a query and TBLASTN search in Cnidarians transcriptomes but the homology of SCRiPs from different species is very low. An identifying feature for both Ueq 12-1 and SCRiPs is a triplet of cysteines located in the C-terminus (Figure  9 ). Since all SCRiPs sequences are deduced from cDNA, no data is available regarding their function and spatial structure. SCRiPs contain only eight cysteine residues, and their distribution is similar to the eight C-terminal cysteines of Ueq 12-1 (Figure  9 ).
38) for the peptides that have a defensin-structure domain such as the mouse alpha-defensin 4 (1tv0), DLP-2(4) (1zue, 1zuf) and hBD2 (1e4q), and it was very low (~0. 25) for the sea anemone defensin-like peptides anthopleurin-A (1ahl) and CGNA toxin (2h9x). For comparison, the Q-score for the structural alignment of anthopleurin-A (1ahl) and CGNA toxin (2h9x) was 0. 7; for DLP-4 (1zuf) and hBD2 (1e4q) it was 0. 52; and for alpha-defensin 4 (1tv0) and beta-defensin hBD2 (1e4q) it was 0. 47. Table  2. PDBeFold structure alignment results of Ueq 12-1 (PDB ID: 5LAH). The Q-score is calculated as Q = Nalgn × Nalgn/((1 + (RMSD/R 0 ) 2 ) × Nres1 × Nres2) where R 0 = 3 Å, The Z-score measures the statistical significance of a match. The higher Z-score, the higher statistical significance of the match.
The system (Waters) consisted of an Alliance 2690 separation module connected to a 2998 photodiode array detector reading from 190 to 500 nm in 1. 2 nm increments and a ZQ single quadrupole instrument, equipped with an electrospray LC interface. Samples were dissolved in water. The samples were separated using a Waters Sunfire C 18 (5 µm, 2. 1 × 100 mm) column. Linear gradients ran from 5 to 50% MeCN/0. 05% TFA and a flow rate of 0. 2 mL/min. MS analyses were performed in the positive ion mode with a cone voltage of 30 V. N 2 was used as desolvation gas (flow of 1000 L/h) and cone gas (flow of 50 L/h). The data was recorded in the continuum mode of acquisition and the quadrupole scanned from m/z 100 to 2000. Ion signals were recorded using the MassLynx v4. 1 (Micromass) software (Waters, Milford, MA, USA).
The series of multiply charged protonated molecular ions acquired from the scan were used to calculate non-protonated average molecular masses. High resolution mass spectrometry (HR-MS) was conducted using a 1290 Infinity UHPLC system hyphenated with a 6540 Q-TOF mass spectrometer with an ESI ion source, controlled by the MassHunter software (all Agilent, Santa Clara, CA, USA). Linear gradients went typically from 5 to 60% MeCN/0. 1% Formic Acid (FA) with a flow-rate of 0. 4 mL/min and column heated to 40 • C. Acquisition was in the positive ion mode at 2 GHz, drying gas eight L/min, Nebulizer gas 35 Psig, capillary voltage 3. 5 kV, fragmentor 175 V, skimmer 65 V, m/z range varied with a maximum of 50-3200. Drying and nebulizer gas was N 2 and the reference masses were 121. 050873 and 922.
Sequencing and Structure Elucidation Reduction was performed by dissolving ~20 nmol peptide in 100 µL 0. 5 M Tris HCl/1 mM EDTA/6 M guanidine HCl and adding 5 µL 2. 2 M dithiotreitol (DTT; Sigma-Aldrich, St. Louis, MO USA). The mixture was flushed with N 2 to prevent oxidation and incubated for 16 h at 37 • C. The following alkylation was achieved by adding 5 µL 4-vinylpyridine (Sigma-Aldrich, St. Louis, MO USA) and incubating for 20 min at 37 • C. The reaction was stopped by RP-SPE, as previously described, eluting with 80% MeCN/0. 05% TFA. Reduction and alkylation of Ueq 12-1 followed by Edman degradation sequencing were performed at Eurosequence (Groningen, The Netherlands). Protein sequence data are available in the UniProt Protein Database under the accession number C0HK26.
DNA sequencing was carried out using an ABI 3730 DNA Analyzer (Applied Biosystems, Carlsbad, CA, USA). The cDNA sequence of Ueq 12-1 was submitted to EMBL Nucleotide Sequence Database with submission number LT600337. The DNA sequence encoding the peptide Ueq 12-1 was constructed from four synthetic oligonucleotides using the PCR technique. The primers UE-dir1 (GAA GAT CTA TGT GCT ATC CGG GCC AGC CGG GCT GCG GCC ATT GCT CCC GT) containing Met-codon for BrCN cleavage, UE-dir2 (GCC ATT GCT CCC GTC CGA ATT ATT GCG AAG GCG CGC GTT GCG AAT CCG GC), UE-rev1 (GAC TCG AGC TAC GCG CAG CAG CAA CGA TCG CCG GAC GCA TCG CAC CAA TG), and UE-rev2 (CGC ATC GCA CCA ATG ATC GGA GCC GCA ATC ATG AAA GCC GGA TTC GCA AC) were used for PCR fragment amplification. The target PCR fragment was gel-purified and cloned into the expression vector pET32b+ (Novagen, Madison, WI, U.
Bioinformatics The BLAST search engine  [55] , the Antimicrobial Peptide Database  [56] , the InterProScan tool  [57]  and StellaBase  [58]  was used to search for homologues sequences. The SignalP4. 1 server  [59]  was used to predict the potential cleavage site of the signal peptide with the default setting for D-cutoff values and no TM regions selected. The theoretical molecular weight and the pI value of Ueq 12-1 were calculated using the Expasy program  [60] , while ChemCalc  [61]  was employed for theoretical monoisotopic mass elucidation. aeruginosa (ATCC 27853), and Escherichia coli (ATCC 2592). All isolates were grown at room temperature in Mueller Hinton Broth (MHB; Difco Laboratories, Detroit, MI, USA). Peptide concentration was determined by weighing and was diluted in water to a concentration of 200 µM and serial twofold dilutions were made before antibacterial activity testing.
4. Oocytes were impaled with two glass microelectrodes filled with 3 M KCl and connected to a GeneClamp 500 amplifier (Axon Instruments, Union City, CA, USA). Oocytes were clamped at -20 mV, recording of inward/outward currents made at repeated step to -100 mV for 80 ms following voltage ramp from -100 mV to +100 mV for 200 ms every 4 s. Diclofenac (300 µM in Ca 2+ -free solution)  [70]  or Allyl isothiocyanate (AITC, 100 µM in Ca 2+ -free solution)  [71]  were used to activate the channel. Experiments were performed at room temperature (22-24 • C). The data were filtered at 20 Hz and digitized at 100 Hz by an AD converter L780 (LCard, Moscow, Russia) using in-house software.
Acknowledgments: This article is dedicated to untimely deceased E. V. Grishin. This study was partially supported by the  programme of Presidium of RAS "Molecular and Cell Biology ", by the grant SSh-7676. 2016. 4 from the  President of RF. This study was also supported by the  Functional Genomics (FUGE)  programme, and the  Biotek 2021 programme of the Research Council of Norway , project  XBioPepS  (grant No. 208546 ). Y. A. L. , Y. V. K. , Y. A. A. and I. V. M. are grateful to the  Russian Science Foundation  (grant No. 16-15-00167 ) for support of work on fluorescent-based intracellular calcium assays on TRP channels, oocyte electrophysiology and animal testing.
The cyclic AMP response element binding protein (CREB) is a primary hub of activity-driven genetic programs in neurons controlling plasticity, neurogenesis and survival. By contrast, the gene networks coordinated by CREB in astrocytes are unknown despite the fact that the astrocytic CREB is also activity-driven and neuroprotective. Herein we identified the transcriptional programs regulated by CREB in astrocytes as compared to neurons using, as study materials, transcriptome databases of astrocyte exposed to well-known activators of CREB-dependent transcription as well as publicly available transcriptomes of neuronal cultures. Functional CREB signatures were extracted from the transcriptomes using Gene Ontology, adult-brain gene lists generated by Translating Ribosome Affinity Purification (TRAP) and CREB-target gene repositories.
We found minimal overlap between CREB signatures in astrocytes and neurons. In astrocytes, the top triad of functions regulated by CREB consists of 'Gene expression', 'Mitochondria', and 'Signalling', while in neurons it is 'Neurotransmission', 'Signalling' and 'Gene expression', the latter two being represented by different genes from those in astrocytes. The newly generated databases will provide a tool to explore novel means whereby CREB impinges on brain functions requiring adaptive, long-lasting changes by coordinating transcriptional cascades in astrocytes. Since its discovery in the late 1980s, the cyclic AMP-response element-binding protein (CREB) is arguably the most widely studied transcription factor, its two best documented functions being the coordination of liver metabolism during cycles of feeding and fasting 1 , and the regulation of neuronal plasticity-defined as long-term adaptive changes-in several scenarios: development, memory acquisition and consolidation, addiction, circadian rhythms and natural regeneration after injury  [2] [3] [4] [5].
Herein we set out to identify the functional programs coordinated by CREB in astrocytes as compared to neurons. We generated transcriptome databases of rat cortex primary astrocyte cultures treated with NE or FSK in order to, respectively, activate cyclic AMP-independent and dependent pathways, or used over-expression of VP16-CREB, which promotes global expression of CREB-dependent genes regardless of upstream kinases  14  , and should thus faithfully unravel the complete population of ast-CREB-target genes. Since CREB-dependent transcription appears to be highly dependent on the stimulation context  15, 16  , we reasoned that the comparison of different transcriptomes, together with a stringent data mining using publicly available databases of adult genes, would lead us to the core functional signatures of ast-CREB as compared to neu-CREB.
The lists were generated by filtration of DEG lists through the first quartile (Q1) of the translational ribosome affinity purification (TRAP), a repository of adult astrocyte genes that only contains genes undergoing effective translation  17. Second, we examined whether DEG-Q1-TRAP lists were enriched in transcriptomes from adult brains with targeted expression of VP16-CREB in astrocytes  9. 4) The DEG-Q1-TRAP lists for NE, FSK and VP16-CREB were processed independently to identify functional signatures by enrichment analysis using Gene Ontology (GO) with ClueGO v1. 4 and ReviGO softwares. 5) Identification of direct ast-CREB gene target candidates and comparison with neu-CREB targets. Core signatures of ast-CREB-dependent gene candidates, defined as the set of genes common to all stimuli, were generated from the overlapping sections among DEG-Q1-TRAP NE/FSK/VP16-CREB, bioinformatic analysis of promoters  18  , and a database of genes containing CRE sites  19.
Global transcriptome changes upon activation of ast-CREB-dependent transcription. The number of DEGs (p < 0. 05) was 3279 genes in FSK-stimulated astrocytes and 2667 in the NE-treated grouprelative to untreated controls-and 9884 in VP16-CREB over-expressing astrocytes with respect to Null conditions. We selected the genes present in the first quartile of the TRAP list of cortical astrocytes, ordered by expression level. The resulting genes will be referred to as Q1-TRAP genes and the discarded as REST (final lists in Supplementary data S2). The process reduced by approximately 3-times the number of genes per group, with the final numbers being: 3355 VP16-CREB, 1049 FSK, and 822 NE. Finally, we analyzed with PSCAN software the localization of direct CREB-targets throughout the transcriptomes.
In vivo validation. In order to validate our strategy for extraction of adult genetic signatures by using Q1-TRAP, we compared DEG-Q1-TRAP lists with the transcriptomes of Gfa2-TtA/TetO-VP16-CREB transgenic mice, which express VP16-CREB in astrocytes linked to the activity of a gfap-based promoter, such that VP16-CREB expression is conditional to astrogliosis  9. In the existing databases, VP16-CREB expression was achieved by acute injury caused by cryolesion (GSE68187). Using Gene Set Enrichment Analysis (GSEA)  20  , we compared the transcriptomes of transgenic versus wild-type mice subjected to cryolesion (TC-WTC group) with the in vitro gene lists (NE-CT, FSK-CT, VP16-Null) filtered by Q1-TRAP. GSEA showed a positive enrichment of in vitro gene lists in the portion of up-regulated genes in the group TC/WTC ('positively correlated' segment in Fig.
Ast-CREB and neu-CREB regulate distinct programs. In parallel we set out to identify direct ast-CREB targets upstream from global functional changes. The premises were: (i) gene targets should be concentrated in the UP sections of the post-Q1-TRAP transcriptomes as predicted by the PSCAN analysis (Fig. 2 ), (ii) harbor Table  1. GSEA of in vitro DEG-Q1-TRAP lists in Gfa2-TtA/TetO-VP16-CREB mice. In vitro databases were compared with UP and DOWN genes in injured transgenic (TC) vs injured WT mice (WTC), and with UP genes in WTC vs WT mice. NES: normalized enrichment score. NOM p-val: normalized p-value. CRE-sites in their promoters and (iii) be up-regulated by FSK, NE and VP16-CREB thus representing the core targets of ast-CREB independently of specific regulatory contexts. The transcriptomes of FSK vs control, NE vs control and VP16-CREB vs Null shared 413 genes of which 125 were up-regulated in the three conditions; 71 are listed in the Salk Institute database as CREB-dependent genes  19.
The lower the p-value the greater the density of CRE-sites (Fig. 6c, d ). To generate the core molecular signature of neu-CREB, we identified CREB-target genes in the UP genes common to FSK and VP16-CREB, using the repository of the Salk Institute. There were 93 genes common to FSK and VP16-CREB. Of the 93 genes, 60 were up-regulated in both VP16-CREB and FSK lists, of which 39 appeared in the Salk Institute databases. As expected, core genes regulated by neu-CREB were the ones traditionally associated with CREB in the brain: Fos, nuclear receptors (Nr4a1, Nr4a2), neuropeptides (Tac1, Npy, Sst) and dual specificity phosphatase (Dusp1) (Supplementary data S4). The functional categories over-represented in the molecular core of neu-CREB were 'Neurotransmission' (12 genes related to well-known neurotransmitters), 'Signalling' (11 genes related to kinases/phosphatases) and 'Gene expression' (6 out of 7 genes encoding for transcription factors), the top ranking genes being Tac1, Dusp1 and Nr4a1.
However, although a wealth of data demonstrates that astrocytes regulate neurotransmission  28  , it is barely recognized that adaptive changes driven by gene expression may happen in astrocytes themselves. Astrocytes have been studied solely in the context of the short-term regulation of synaptic events  29. Indeed, the available GO classification and pathway enrichment repositories like KEGG mirror the current neuron-centric conceptualization of the brain, and hence lack categories related to astrocyte-specific functions and excitability as shown by calcium responses  30. This means that the existing databases are obsolete. Their update will require that astrocytic molecules and pathways controlling circuit long-term plasticity be sufficiently conceptualized and characterized to give rise to novel categories.
Similar results were observed in the FSK group. (c) The same PSCAN analysis without considering bins but entire sets of genes: 'all' , all the genes; 'up' and 'down' , all the up-regulated and downregulated genes independently of the significance of change; 'TRAP' , only the Q1-TRAP list; 'rest' , the remaining genes. The up-regulated Q1-TRAP genes were enriched in CRE sites. (d) Core up-regulated astrocyte genes filtered through the Q1-TRAP list and the CREB-target-gene database (Salk institute) were compared with neuronal databases obtained from neurons treated with FSK or VP16-CREB 10 processed in like manner. Venn diagrams showed almost no overlapping between both cell types. Categories were manually inferred from gene function according to the literature. The full lists are in Supplementary data S4.
Chart slices correspond to the percentage of genes in each category. metabolism via a catecholamine signal originating in neurons  34. The unifying theme of these studies is that CREB mediates adaptive metabolic changes. Here we posit that, in the brain, adaptive metabolic changes mediated by an ast-CREB/mitochondria axis influence memory formation. This is in line with the emerging notion that mitochondria regulate synaptic plasticity by locally controlling energy status and calcium content  35, 36. Of note, hits of the array are Dgat, related to triglyceride synthesis, which has been recently described as an essential requirement for fatty-acid oxidation in the mitochondria  37  , and Gpx4, specialized in reducing lipid-derived reactive oxygen species. All in all, the data suggest that ast-CREB has an impact on astrocyte aerobic metabolism by enhancing mitochondrial fatty-acid oxidation while protecting cells from lipid-derived oxidative stress.