dataesr/scientific-paragraphs-categorization huggingface dataset:
7) was explored with another simulation. This latter simulation was run under constant body temperature of 27 • C and constant food density (f = 0. 925) from metamorphosis to fish death. The initial state of the system agreed with the fish state at metamorphosis, i. e. a maturity level E j H , age of 30 days and fork length of 1. 3 cm from which we deduced a structural length of 0. 33 cm. Both simulations were performed with a 1-day time step using the dde function, a numerical solver for delay differential equations implemented in the PBSddesolve package  [7]  of the R software  [61].
PCR Primers and probes were designed using the Primer Express Software V. 3. 0 (Life Technologies, Saint Aubin, France) to target TEQUI_1010 (O-antigen export system permease protein RfbD, 1052325-1052410), TASI_0169 (Zinc ABC transporter, ATP-binding protein ZnuC, 171816-172112), ecfx (extracytoplasmic function gene, GenBank accession no. DQ996551) and mdh (malate dehydrogenase housekeeping gene, GenBank accession no. AM051124) genes of T. equigenitalis  [20] , T. asinigenitalis  [20] , P. aeruginosa [21] and K. For each experiment, 20 µl of amplification solution (ADIAGENE) was mixed with 5 µl of DNA extract. rtPCR was performed on a QuantStudioTM cycler (Life Technologies) using a program with initial steps at 50°C for 2 min and 95°C for 10 min followed by 45 cycles at 95°C for 15 s and 60°C for 1 min.
Data were analyzed using the QuantStudioTM software (Life Technologies). Each assay included a negative control for the extraction step and negative (Rnase free water) and positive (calibrated DNA extracts) controls for the amplification steps. Characterization of both ADIAVET REAL TIME PCR (ADIAGENE) (i. e. efficiency, repeatability, reproducibility, specificity and limit of detection (LOD)) and the complete analytical method (from DNA extraction to rtPCR analysis) were done according to the French AFNOR Norm  [23]. To evaluate specificity, 24 different stains of T. equigenitalis, 14 of T asinigenitalis, 33 of K. pneumoniae and 16 of P. aeruginosa were used. The LODMethod was determined using 3 five-fold serial dilutions of calibrated bacterial suspension added to a negative emulsion of swabs or semen.
, 2008) , and their stability was validated using the Ct method described by  Silver et al. (2006). Briefly, a qPCR was carried out for the three housekeeping genes on all samples and tub-b was selected as constitutive gene for normalization, because tub-b expression was not affected by the treatments (i. e. , lowest standard deviation among the housekeeping genes tested). For the gene expression analysis, Light Cycler 480 SV1. 5. 0 software (Roche) was used to extract Ct values based on the second derivative calculation and the LinReg software version 11. 0 was used to calculate reaction efficiencies for each primer pair  (Ruijter et al. , 2009). The relative expression level (fold change) of each gene was then calculated according to the Pfaffl equation  (Pfaffl, 2001)  for tagatose-incubated samples as compared to the respective control samples (calibrator) for each time point and Phytophthora spp.
Statistical Analysis All experiments were carried out twice and data were analyzed with Statistica 13. 1 software (Dell, Round Rock, TX, United States). Normal distribution (Kolmogorov-Smirnov test, P > 0. 05) and variance homogeneity of the data (Levene's tests, P > 0. 05) were checked and parametric tests were used when both assumptions were respected. Each experimental repetition was analyzed singularly and a two-way analysis of variance (ANOVA) was used to demonstrate non-significant differences between the two experiments (P > 0. 05). Data from the two experimental repetitions were pooled and significant differences were assessed with the Student's t-test (P ≤ 0. 05) or Tukey' test (P ≤ 0. 05) in case of pairwise or multiple comparisons, respectively. Fold change values of gene expression analysis were transformed using the equation y = Log 10 (1 + x)  (Casagrande et al.
RESULTS Tagatose Differentially Inhibits Phytophthora infestans and P. cinnamomi Growth and Causes Ultrastructural Alterations Phytophthora infestans growth was inhibited by tagatose at 4 and 10 DAI and the level of inhibition using 5 and 10 g/L tagatose was comparable at each time point (Figure  1A ). Conversely, P. cinnamomi growth was not affected by 5 and 10 g/L tagatose at 10 DAI, and only a slight inhibition was observed with 10 g/L tagatose at 4 DAI (Figure  1B ). When transferred to new PAM dishes, the growth of P. infestans plugs collected at 10 DAI with 5 and 10 g/L tagatose was comparable to the growth of P. infestans plugs collected at 10 DAI from control dishes (data not shown), indicating that the effect of tagatose was reversible. In order to verify the specificity of tagatose, isomers were tested, such as fructose, psicose, and sorbose.
The incubation with 5 g/L fructose, 5 g/L psicose, or 5 g/L sorbose did not inhibit P. infestans and P. cinnamomi growth at 4 DAI (Supplementary Figure  S1 ) and 10 DAI (data not shown). Because the minimum dosage showing a differential effect on Phytophthora spp. growth was 5 g/L tagatose (Figures  1C, D ), this quantity was selected for the following experiments. In order to investigate morphological impacts of tagatose incubation on cellular structures, TEM analyses were carried out. The typical ultrastructure of Phytophthora spp. (Xu et al. , 2007)  was observed by TEM analysis of P. infestans collected at 4 DAI (Figures  2A, B ) and 10 DAI in PB (Figures  2C, D ). Conversely, the structure of mitochondria was severely altered in tagatoseincubated P. infestans samples, displaying the reorganization of mitochondrial cristae at 4 DAI (Figures  2E, F ) that leads to circular and concentric cristae at 10 DAI (Figures  2G, H ).
The sexes show profound differences in responses to infection and the development of autoimmunity. Dimorphisms in immune responses are ubiquitous across taxa, from arthropods to vertebrates. Drosophila melanogaster shows strong sex dimorphisms in immune system responses at baseline, upon pathogenic challenge, and over aging. We have performed an exhaustive survey of peer-reviewed literature on Drosophila immunity, and present a database of publications indicating the sex(es) analyzed in each study. While we found a growing interest in the community in adult immunity and in reporting both sexes, the main body of work in this field uses only one sex, or does not stratify by sex. We synthesize evidence for sexually dimorphic responses to bacterial, viral, and fungal infections. Dimorphisms may be mediated by distinct immune compartments, and we review work on sex differences in behavioral, epithelial, cellular, and systemic (fat body-mediated) immunity.
The de novo MG reconstruction was also applied to colony LM1 at sampling point LM1_8 and it yielded 211,724 ORFs annotated on 64,347 contigs for the total assembly size of 177. 5 million base pairs (Mbp). For both datasets, initial public database-dependent taxonomic classification of genes and gene transcripts pointed to the abundance of Firmicutes (Supplementary Fig. 4 ), what contrasted the results of community structure analysis. Subsequent binning of MG contigs and phylum-level annotation of the resulting bacterial bins allowed assigning correct taxonomic origin, confirming the metagenomic abundance of Spirochaetae and Fibrobacteres (Fig. 1c ; Supplementary Fig. 5 ). Following mapping of RNA reads to the MG assembly (referred to as "RNAseq" analysis), we could confirm transcriptional dominance of these two bacterial phyla as well.
Incomplete public databases and extensive horizontal gene transfer were previously proposed as the origin of this misclassification  9. Based on the classification of genes and transcripts to broad functional categories such as KEGG ontology profiles (KOs), congruency between the de novo MG and MT reconstructions was high (Supplementary Fig. 6 ). However, out of the de novo MT reconstructed gene transcripts of prokaryotic origin, only 37. 8% showed significant similarity to the de novo MG genes at the protein level (blastp e-value ≤ 10 -5 ), sharing on average 76. 04% of amino acid identity (Supplementary Fig. 4 ). Coherent to our study, differences in functional gene profiles between MG and MT reconstructions have been previously underlined  13. Even in the context of the termite gut, some authors highlighted the value of the de novo MT assembly in retrieving highly expressed genes  9, 14.
Genomic potential and transcriptional adaptation of gut microbes. Aggregation of 68. 9 ± 1. 8% of the de novo reconstructed gene transcripts into clusters of orthologous genes (COGs) pointed at functional microbiome stability at the different stages of feeding campaign (Supplementary Data 3). Consistently with previous reports  11, 14, 15  , cell motility and chemotaxis together with carbohydrate transport and metabolism were the two most highly expressed gene categories. Reconstruction of (nearly) complete metabolic modules was quite similar between Fibrobacteres and Spirochaetae. However, further comparative analysis using LEfSe (Fig. 2 ; Supplementary Data 4 and 5) identified several biologically informative features differentiating these two bacterial phyla. Both were capable of nitrogen fixation and glycogen synthesis, but the two pathways were enriched in Fibrobacteres.
2 ; Supplementary Data 4). Multiple sugar ABC transporters were up-regulated in the Spirochaetae metatranscriptome, while they were nearly absent from the MG and MT reconstructions of Fibrobacteres origin. This observation could suggest the governance of exogenous carbohydrates uptake and utilisation by Spirochaetae. Diversity and abundance of termite gut microbial CAZymes. The de novo MT reconstruction yielded over 2000 of manually curated transcripts assigned as CAZy-coding genes (cazymes). Out of these, 38. 4% were further assigned to 55 GH families. The de novo MG reconstruction resulted in close to 7000 different cazymes, 43. 6% of which were assigned to 86 GH families (Supplementary Figs. 6  and 7 ). Although there was a good correlation between the distributions of identified GHs to different GH families (Pearson r 0.
83), roughly 150 cazymes identified in the de novo MT were also reconstructed from the assembled metagenome. Novelty of reconstructed cazymes was evidenced through sequence comparison to NCBI refseq database, and a metagenomic dataset previously generated for Nasutitermes sp. 15  (Supplementary Fig. 4 ). In the latter case, average amino acids identity for the 943 query hits equalled 65. 4 ± 19. 9% (blastp, e-value ≤ 10 -5 ), pointing to the diversity of microbial cazymes in guts of different termite species, even those phylogenetically closely related. Differential expression of specific cazymes at different stages of the feeding experiment suggested quick acclimation to new (laboratory) conditions, also reflecting adaptation of gut microbes to digest Miscanthus (Fig. 3 ). There were roughly 29.
We hypothesise that closely related Spirochaetae strains contain highly similar GH11 genes, possibly shared by horizontal gene transfer; likewise, it was shown for e. g. human gut Bacteroidetes  17. Their conserved nature may impede proper gene reconstruction from sequencing reads, similarly to other structurally conserved genes such as 16S rRNA or transposase, that typically do not reconstruct into larger genomic fragments  18. GH45 was only present in Fibrobacteres and it was the second most expressed GH family under Miscanthus diet. According to the CAZY database, nearly 95% of proteins assigned to this family are of eukaryotic origin (Supplementary Fig. 10 ), and show endocellulase activity. Previously, GH45 CAZymes were characterised from lower termite symbiotic protists  19. Lytic polysaccharide monooxygenases (LPMOs) typically assigned to AA9 (fungal) and AA10 (predominantly bacterial enzymes) families  20  were neither present in the reconstructed metagenome nor metatranscriptome.
3 ± 2. 2% of gene transcripts classified as GHs. In many cases, these predictions were experimentally validated (Supplementary Data 6). We confirmed β-glucosidase, endocellulase, endoxylanase and arabinofuranosidase activities of several Spirochaetae CAZymes. We also characterised active endoxylanases and endomannanases from Fibrobacteres. Abundance of transcripts associated with endocellulase (EC:3. 2. 1. 4) and endoxylanase (EC:3. 2. 1. 8) increased under Miscanthus diet (for both Fibrobacteres and Spirochaetae), while those involved in chitin and starch (α-glucans) degradation decreased (Fig. 4 ; Supplementary Fig. 12 ). Endocellulase-assigned transcripts were nearly equally abundant between Fibrobacteres and Spirochaetae, while abundance and diversity of endoxylanases of Spirochaetae origin was much higher.
Putative cellulose-utilisation gene clusters were the most highly expressed in Fibrobacteres MAGs, suggesting its major contribution to cellulose degradation (Figs. 3  and 4 ). Endoxylanase-encoding genes were often colocalised with endocellulases (Supplementary Data 7); however, xylosidases were scarce, questioning the ability of Fibrobacteres to utilise complex xylans. Cazymes clusters targeting among others alpha glucans, (arabino)xylans (AX), beta glucans, cellulose, chitin, galactans, mannans and xyloglucans were evidenced in reconstructed Spirochaetae genomes. Largely complete AX-targeting clusters were assigned to MAG_17 and MAG_1, both representing Treponema. All of them were transcriptionally up-regulated under Miscanthus diet (Supplementary Fig. 15 ), what is consistent with high AX content of Miscanthus hemicellulose.
Host functional gene expression profiles under Miscanthus diet. Following taxonomic annotation, 16,416 gene transcripts of eukaryotic origin were classified to Arthropoda. Based on the presence of 271 conserved orthologous reference eukaryotic genes  26  , we estimated the completeness of our termite gut epithelial transcriptome (relative to midgut and hindgut) at 89. 5%, while the contamination with foreign mRNA was below 0. 7%. Number of assembled ORFs was in line with the two published termite genomes, Macrotermes natalensis (16,140 protein-coding genes; ref. 27  ) and Zootermopsis nevadensis (15,459 protein coding-genes; ref. 28  ; Supplementary Data 9 and Supplementary Fig. 16 ). However, it was much lower than for another sequenced lower termite genome of Cryptotermes secundus (26,726 protein coding-genes; accession number PRJNA432597).
15 ). Based on the diversity and expression patterns of GHs, different sugar transporters (mainly ABC and to a lesser extent PTS; Supplementary Data 8) and specific sugar isomerases, Spirochaetae are able to utilise a wider range of Miscanthus-derived sugars (including glucose, glucoronate, rhamnose, arabinose, mannose, xylose, ribose and fucose) than Fibrobacteres (mainly glucose, mannose and possibly ribose). Both bacterial phyla can target the backbone of cellulose, xylans and mannans (the latter is not abundant in Miscanthus biomass). Enrichment of Fibrobacteres metatranscriptome in endoglucanases (both targeting 1-3 β and 1-4 β glycosidic bonds as present in β-glucans and cellulose, respectively) shows its preference for carbohydrates with a glucose-unit backbone. Fibrobacteres also express endoxylanases, and we could confirm experimentally xylanase activity for one GH11 enzyme (Supplementary Data 6).
9. Based on the in silico prediction of enzyme sub-cellular localisations, most of the endoxylanases from Fibrobacteres and Spirochaetae are exported outside the cell (Supplementary Data 10), suggesting initial degradation of xylan backbone in the extracellular space. Many Spirochaetae endocellulases are also putative extracellular enzymes or anchored to the outer membrane. In contrast, multiple Fibrobacteres endocellulases possibly lack signal peptide and are assumed to be localised in the cytoplasm. In general, as much as half of Fibrobacteres GHs are predicted to be localised in cytoplasm. At the same time, three times more GHs are exported outside the cell by Spirochaetae. This could indicate a rather selfish carbohydrates degradation strategy employed by termite Fibrobacteres, where cellulose fibres primarily detached by extracellular endocellulases are transported inside the cell for further breakdown.
To assure the proper disruption of bacterial cell wall and termite gut epithelium cells, mechanical bead-beating step with 0. 1 mm glass beads at 20 Hz for 2 min was introduced to complement the chemical lysis. The eluents were divided in two parts. First part was treated with 1 µL of 10 µg/mL RNase A (Sigma) for 30 min at room temperature. The second part was treated with TURBO DNA-free kit (Invitrogen) according to the manufacturer's protocol. The resulting pure DNA and RNA fractions were quality assessed using agarose gel electrophoresis and Bioanalyser RNA 6000 Pico Kit (Agilent). Nucleic acid concentration was quantified using Qubit dsDNA HS Assay and Qubit RNA HS Assay Kit (Invitrogen). DNA and RNA were stored at -20 °C and -80 °C, respectively. 16S rRNA gene amplicon high-throughput sequencing and data analysis.
7. 0. 1090_win64 software  51  was used for quality trimming, chimera check, singletons removal and assignment of the obtained sequences to OTUs at 97% similarity level. Taxonomic affiliation of the resulting OTUs was performed with SILVA database v. 128 (ref. 52 ). Downstream analyses were performed with mothur  53  and R environment  54. Bacterial richness and diversity were calculated using respectively sobs and invsimpson indices. The dissimilarity of bacterial community structures was calculated using the Bray -Curtis index. OTUs differentially abundant between the wild-and Miscanthusadapted microbiomes were assessed using the LEfSe approach  12. De novo metagenomics and data analysis. Sample LM1_8 was selected for metagenomic sequencing in order to reconstruct genomes/larger genomic fragments of the dominant microbes in the Miscanthus-adapted microbiome.
ORFs were searched and annotated using the default pipeline integrated in the IMG/MER  55. Information about KEGGs and COGs assignment was retrieved based on the IMG/MER annotations. Metabolic pathways/modules were reconstructed using the tool integrated in the online version of the KEGG database  56. Initially, contigs were binned using myCC  57  what resulted in their separation into 35 phylum-level bins of relatively high contamination. This approach was undertaken to correctly assign phylum-level taxonomy to the resulting contigs. Subsequently, the bin refinement module integrated in MetaWRAP was used to fine-tune the resulting bins (MAGs) to the species/ strain levels  58. The completeness and contamination of the generated MAGs were assessed with checkM  59. Taxonomic affiliation was assessed with PhyloPhlan  60.
Similarity to the previously reconstructed MAGs was verified with the FastANI  61. MAGs abundance within the reconstructed metagenome was calculated as average of contigs metagenomic abundance (DNA-RPKMs, see above) assigned to a specific MAG. Given the relatively high microbial diversity in the termite gut, only 54. 6% of the resulting MG sequencing reads could map back to the reconstructed MG contigs, potentially mitigating the rate of functional gene discovery if solely relaying on the de novo MG reconstruction. Phylogenetic analyses were performed on MAFFT-aligned protein sequences  62  using MEGA X  63. De novo metatranscriptomics, host transcriptomics and data analysis. For three selected samples (LM1-1, LM1-2 and LM1-8) the (meta)transcriptomic analysis was performed using an optimised approach described earlier  11.
Contaminating rRNA reads were removed using SortMeRNA 2. 0 software  64. The resulting non-rRNA reads were used to perform de novo (meta) transcriptome co-assembly using the CLC assembly algorithm in mapping mode with default parameters, except for minimum contig length of 200, length fraction of 0. 90 and similarity fraction 0. 95. As a result, nearly 2 million contigs were assembled. Obtained contigs were further submitted to IMG/MER for taxonomic and functional annotation  55. Following the taxonomic assignment, 759,451 transcripts of putative prokaryotic origin were selected for further analysis. Initial IMG/MER taxonomic annotation resulted in over-representation of transcripts of putative Firmicutes origin (Supplementary Fig. 4 ). As nearly no Firmicutes OTUs were detected using the 16S rRNA gene amplicon sequencing, transcripts were re-annotated based on the de novo assembled metagenome and contig binning, resulting in re-classification of virtually all Firmicutes-assigned contigs to Fibrobacteres and Spirochaetae.
To complement the study and to characterise potential contribution of the termite host to Miscanthus digestion, transcripts of eukaryotic origin and taxonomically assigned to Insecta (based on the IMG/MER annotation) were further evaluated for the completeness of the de novo reconstructed transcriptome with the BUSCO pipeline  26  and using the Eukaryota database (odb9). There were only two duplicated genes out of the total of 303 searched groups, suggesting that the level of possible contamination of non-Insecta origin was very low (below 0. 7%). For both the de novo assembled metatranscriptome and termite transcriptome, in order to determine the relative abundances of transcripts across studied samples, sequencing reads were mapped back to the annotated transcript sets, using the CLC "RNA-seq analysis" mode, with default parameters except for minimum similarity of 0.
95 over 0. 9 of the read length, both strands specificity and 1 maximum number of hits per read. The mapping results were represented as TPMs (transcripts per million), what directly resulted in normalised reads counts. Identification of cazymes and enzymes characterisation. Genes (metagenomics) and gene transcripts (metatranscriptomics) encoding for microbial CAZymes were detected using dbCAN (dbCAN-fam-HMMs. txt. v6; ref. 65  ) and CAZy database  66. Using the threshold of e-value of <1e -18 and coverage >0. 35 recommended for prokaryotic CAZymes resulted in the removal of a high number of putative CAZymes; therefore, additional manual curation was performed to maximise the number of entries retained for further analysis. Additionally, gene transcripts outliers (very partially reconstructed gene fragments with average MT expression significantly exceeding the average expression of other genes assigned to the same group) were manually identified and removed as they were considered as chimeric (additional Blast search was launched in each case).
Data availability The raw sequencing data used in this study were deposited in the SRA database under the following project numbers: PRJNA587606 (16S rRNA amplicon sequencing), PRJNA587423 (Metagenomics) and PRJNA587406 (Metatranscriptomics). OTU sequences were deposited in GenBank under project numbers PRJNA586754 and PRJNA434195. COII nucleotide sequences are available in GenBank under accession numbers MN803317-19. MG and MT assemblies and all other data underlying the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgements This research was funded through FNR 2014  CORE  project  OPTILYS  (Exploring the higher termite lignocellulolytic system to optimise the conversion of biomass into energy and useful platform molecules/ C14/SR/8286517 ), and co-funded through the grant  PDR T. 0065. 15from the  Belgian F. R. S. -FNRS. We are grateful to  Philippe Cerdan ,  Régis Vigouroux  and the staff of the  Laboratoire Environnement HYDRECO of Petit Saut (EDF-CNEH)  for logistic support during the field work.