dataesr/scientific-paragraphs-categorization huggingface dataset:
We chose over 10,000 isolates of S. enterica for genome sequencing (Table  1  and Table 2 ), with priority given to isolates whose DNA had previously been isolated and 7-gene MLST performed. Once those samples had been processed, DNAs were isolated from additional strains in the collections in Table  1. DNA concentrations were calibrated with Pico Green fluorescence to ensure that each sample contained at least 400 ng of DNA. Each sample was diluted into two 0. 5 ml FluidX screw-capped, 2-D bar-coded tubes. One set of duplicate tubes was shipped to the Sanger Institute, Hinxton, UK for draft genome sequencing, and the second was maintained as a reserve at University of Warwick. Post-sequencing procedures. Sets of short reads were extracted from the storage system at the Sanger Institute with the "path-find" module (Bio-Path-Find), and uploaded into EnteroBase together with the corresponding metadata that had been stored in the BioNumerics database.
Draft Manual curation. Manual curation of the assembled genomes was performed within EnteroBase to generate the most accurate dataset that was possible. Where the data were available, we compared the genome-derived predictions for each isolate with serotype assignments from laboratory experiments and/or historical MLST data. To this end, we created a custom view and user-defined fields that contained an arbitrary sequential Plate number for each rack of 96 tubes (95 DNAs plus a blank in microwell format, i. e. from A1 to H12) and information on the rows and columns of the tubes as well as their barcodes. We created one workspace for all the strains and their sub-strains for each microwell rack. 7-gene MLST data from the older ABI-based sequence data were compared with 7-gene MLST predictions from the genome assemblies.
Data availability Underlying data Short read sequences are available for public access at the Short Reads Archive (SRA) at EBI under BioProject accessions PRJEB20997 and PRJEB33949. NCBI BioProject: Salmonella enterica ancient DNA and modern demography. Accession number: PRJEB20997 NCBI BioProject: EnteroBase -User Uploads from M. Achtman to EnteroBase Salmonella database. Accession number: PRJEB33949 All other data is available for public access in EnteroBase http://enterobase. warwick. ac. uk in the Salmonella database. Individual strains and genomes from this project can be located with the same BioProject accession codes and also by the metadata field containing the text "M. Achtman". All the analyses described were performed with software that are available within EnteroBase. Access to the individual trees with the option of colour-coding by other metadata is publicly accessible at: In this major study, the Achtman group have assembled a fascinating collection of 10,000 Salmonella isolates that spanned more than a century, and were obtained from a wide range of mammalian, reptilian and environmental sources.
○ On page 14, the important manual curation process is described. I suggest that an additional sentence is added at the beginning of this section to clarify the rationale of this approach for readers. One option would be to begin "Manual curation of the assembled genomes was performed within EnteroBase to generate the most accurate dataset possible. For individual genomes to be assigned to the final dataset, the genome-derived predictions needed to be consistent with either serotype or MLST data for each isolate. To this end…", but of course the authors should make the sentence their own.
Acknowledgements We gratefully acknowledge the receipt of additional bacterial strains from  Gail Wise ,  VLA -Weybridge, UK ;  Beverley C. Millar ,  Northern Ireland Public Health Laboratory, Belfast, UK ;  Finola Leonard ,  UCD, Dublin, Ireland ;  Lee Harrison ,  University of Pittsburgh School of Medicine and Graduate School of Public Health, Pittsburgh PA ;  John Wain ,  PHE -Colindale, UK ;  Mary Murphy ,  Veterinary Food Safety Laboratory, Inniscarra ,.
Plasmid transfer The IncC plasmid, pPV835TEM24 (GenBank accession number MN148427), originally from a Proteus vulgaris strain, Pv835, was used to induce IME excision. It harbours a floR gene encoding for chloramphenicol and florfenicol resistance, an aacA4 gene encoding kanamycin, tobramycin, netilmicin and amikacin resistances, a dfrA1 gene encoding trimethoprim resistance, an aadA1 encoding streptomycin, spectinomycin resistances and a sul1 encoding sulphonamides resistance. The Enterobacter aerogenes BOL (EABOL) strain harbouring the IncC plasmid pPV835TEM24 (donor) was mated with the Proteus mirabilis Pm1LENAR which had an IME (recipient) in a 4:1 ratio at the end of the exponential growth phase in Luria Bertani broth at 37°C as previously described  (Siebor et al. , 2016). After overnight incubation at 37°C without shaking of the mating broth, 10-fold serial dilutions of the bacterial cells were plated on Drigalski agar media (ThermoFisher Scientific®) (which inhibits the swarming of P.
Nucleotide sequence accession numbers The nucleotide sequences of the complete SGI0 and the pPV835TEM24 plasmid were assigned the GenBank accession numbers MH734355 and MN148427, respectively. The Whole Genome Shotgun project for the Pm1LENAR strain has been deposited at DDBJ/ENA/GenBank under the accession VIYO00000000. The version described in this paper is version VIYO01000000.
In this isolate, the presence of a SGIlike structure was found using an SGI1-fingerprinting assay but the class 1 integron was not detected  (Amar et al. , 2008). However, no sequence is available. A later study detected the presence of an SGI-like element without a class 1 integron in a P. mirabilis isolate, which was collected from a dog in 2013, in France  (Schultz et al. , 2015). Only 3. 9 kb of this structure was sequenced (some parts of S007 (sgaD), S008 and S011) (GenBank accession number KR296941). Interestingly, these parts are identical to the corresponding parts of SGI0, reported here and it might be identical to SGI0. The isolate harbouring this SGI, came from a different area (Pyrénées orientales) than ours (Bourgogne). However, like Pm1LENAR, this isolate was also resistant to amoxicillin, amoxicillin + clavulanic acid, kanamycin, spectinomycin, trimethoprim.
Necropsies were usually performed within a few hours after death but some were delayed for periods up to 24 hours. About 90% of the equids examined were from Normandy, which is the leading horse breeding region in France with roughly 10,500 foal births per year. For every animal, relevant metadata including age, sex, breed, date of death, original stud farm were recorded. Indications about the last anthelmintic treatment administered were also collected in most cases. A few observations were discarded before analysis, including an individual whose age was unknown and 32 records collected from geldings (as it was not possible to estimate any sex effect with so few observations). In addition, 33 cases from a bankrupted stud farm and one horse from a farm where no anthelmintic drug were given were also removed from the dataset to avoid spurious signal linked to a lack of parasite management.
This certainly reflects the important contribution of race horses to our dataset (84%), as these are usually subjected to intensive deworming programs. For instance, a 2013-survey across eight French Trotter studs revealed that foals were given eight anthelmintics a year  (Sallé et al. , unpublished observations). Of note, a significant break in non-strongylid prevalences has occurred within a ten-year window ranging from 1998 to 2008, whereby Parascaris spp. arose in contrast to bots and tapeworms that suffered strong reduction in their respective prevalences. The sharp decline of tapeworm prevalence followed closely the release of praziquantel between 2001 and 2005, commercialized either alone (marketing authorization number FR/V/8052367 3/2001) or combined with ivermectin (marketing authorization number FR/V/1889939 3/2004) or with moxidectin (marketing authorization number FR/V/3281212 3/2005).
Discussion Orthopteran insects, such as crickets, katydids and grasshoppers, have been model systems for studying acoustic communication for decades  2, 7, 11, 18, 30, [43] [44] [45] [46]  , but how hearing and sound-producing organs originated and evolved throughout the diversification of these insects has remained elusive due to the lack of a wellresolved phylogeny. This work firmly establishes phylogenetic relationships among the major lineages and divergence time estimates within Orthoptera based on phylogenomic data and carefully selected fossil calibration points. We find that crown-Orthoptera likely originated 355 million years ago, and diverged into Ensifera and Caelifera in the Carboniferous (Fig. 1 ). Our study suggests that these two suborders have each followed very different, lineage-specific patterns of evolution for hearing and sound-producing organs (Figs.
Therefore, our study finds a pattern consistent with what was shown in tetrapods  4  in that we find little evidence that acoustic communication alone increased net diversification. Our results have a major implication in enhancing our understanding of signal sender-receiver co-evolution and diversification in Orthoptera, revealing more general insights about the evolution and mechanisms of animal communication. 5 rate categories, empirically estimated base frequencies (model = 2) and allowed rates to be inferred from individual sites (RateAncestor = 1). We conducted Hessian matrix calculations according to the above specifications with CODEML as implemented in PAML using empirical +F base frequencies estimated from the respective data set. MCMC chains ran for 1,000,000 generations (sfreq = 50) while discarding a burn-in of 100,000 generations.
We fitted a continuous-time Markov chain (Mk) singlerate (ER) model to our data to infer character evolution using the R package phytools  102. Using the same data set, we also performed Pagel's 37 binary character correlation test for the evolutionary correlation between hearing and sound production, using phytools. We pruned the phylogenetic tree to create Orthopteraonly, Ensifera-only and Caelifera-only data sets to compare and contrast lineagespecific patterns. We recoded different types of tympanal and stridulatory mechanisms as simple presence-absence binary characters for both hearing and sound production to reveal the general co-evolutionary dynamics of these two traits. For each data set, we fitted four models of co-evolution between hearing and sound production and compared the results using the Akaike Information Criterion (AIC): (i) hearing and sound production evolve independently; (ii) the evolution of hearing depends on the evolution of sound production; (iii) the evolution of sound production depends on the evolution of hearing; and (iv) hearing and sound production evolve interdependently.
Rhaphidophoridae have the SGO and the IO, with no obvious trace of specialised auditory receptor cells  103. Schizodactylidae, Gryllacrididae, Stenopelmatidae and Anostostomatidae all have the sensory organ similar to that of Tettigoniidae, consisting of the SGO, the IO and the sensory neurons that are homologous to the CA, but with no auditory specialisation, called the crista acustica homologue (CAH)  69, 104. Because we did not have detailed neuroanatomical data for our taxon sampling, we could not perform ancestral character state reconstruction of the complex tibial organ in Ensifera, but we were able to map this character on the phylogeny based on the assumption that the configuration would be conserved at the taxonomic family level. To estimate the rates of lineage-specific diversification, we performed a diversification analysis using the program Bayesian analysis of macroevolutionary mixtures (BAMM)  39  and the R package BAMMtools 105.
We used "speciationextinction" as a model for the diversification analysis in BAMM, and ran for 10 million generations with a sampling frequency of 1000. Convergence assessment, analysis of rate shifts, and calculation of clade-specific rates were performed using BAMMtools. To test whether the evolution of hearing and sound production has affected speciation and extinction rates, we fitted models of trait-dependent diversification using the R package hisse  42. Because it has been shown that the presence of unmeasured factors (or hidden states) could impact estimation of diversification rates for any observed trait when analysed under the framework of BiSSE (Binary State Speciation and Extinction) methods  107  , we adopted a multimodel inference method, implemented in HiSSE (Hidden State Speciation and Extinction)  42.
We first pruned the time-calibrated ultrametric tree to only include Orthoptera (239 terminals), and used the binary character data sets for hearing and sound-producing organs previously used for the Pagel's test. Because the presence of these organs does not necessarily indicate the presence of acoustic communication, we created an additional data set to code acoustic communication as a binary character to test if its evolution affected the diversification rate. We fitted 24 different models, used in Beaulieu and O'Meara  42  , to both the hearing data set and the sound production data set for Orthoptera. These models included four models corresponding to BiSSE models, four models corresponding to trait-independent models (described as CID models), and 16 models corresponding to different HiSSE models that assumed a hidden state associated with both the observed states.
Acknowledgements The authors extend their gratitude to all those who assisted with any aspect of this project, from specimen collection, to molecular lab work, to bioinformatics, divergence time estimates and all our analyses. We would like to thank the entire 1KITE consortium [https:// www. 1kite. org/],and especially  Karen Meusemann  for the tremendous help during all steps of this study. We thank the following collaborators who assisted with specimen acquisition and determination:  Christina Painting ,  Anna Probert ,  David Weissmann ,  Dezhi Zhang ,  Boyang Ding ,  Dieter Schulten ,  Geoff Monteith ,  Hans Pohl ,  Hong Yin ,  Kai Schuette ,  Karl Kjer ,  Kevin Judge ,  Luke Dunning ,  Craig Williams ,  Philipp Krohn ,  Dietrich Ober ,  Ralph S. Peters ,  Thomas R. Buckley ,  Victoria Twort ,  Xinjiang Li ,  Pengxiang Wang ,  Yongchao Zhi ,  Dezhi Zhang , and other colleagues from  BGI-Shenzhen  who contributed to sample and data curation and management.
Data availability All data sets generated and/or analysed during this study, including those related to phylogenomic analyses, divergence time estimation, and character evolution analyses, have been published in Dryad Digital Repository [https://doi. org/10. 5061/dryad. qjq2bvqc6]. All transcriptome and mitochondrial genome data, both newly sequenced and previously published, can be accessed at NCBI databases and specific accession numbers with hyperlinks can be found in Supplementary Data 1 and 3. Furthermore, additional information related to methods and analyses is included in Supplementary Information and Supplementary Data.
Code availability All scripts for the phylogenomic pipeline, including alignment refinement, protein domain identification, alignment masking, optimizing data sets and topological tests haven been previously published [https://doi. org/10. 1126/science. 1257570] and can be accessed [https://www. zfmk. de/en/research/projects/1kite-the-evolution-of-the-insects]. In addition, we used following published custom code: AliCUT v2. 3 [https://github. com/ PatrickKueck/AliCUT] SymTest v. 2. 0. 47 [https://github. com/ottmi/symtest], MitoZ [https://github. com/linzhi2013/MitoZ], selectSites. pl [https://github. com/justincbagley/ MAGNET/blob/master/perl/selectSites. pl], pfam_scan. pl [http://ftp. ebi. ac. uk/pub/ databases/Pfam/Tools/] and plot_runs_MCMCtree. R [https://github. com/kmeusemann/ scripts/blob/master/plot_runs_MCMCtree.
Methods Phylogenomic analyses and divergence time estimation. Our taxon sampling consisted of 239 species of Orthoptera and 10 polyneopteran outgroups, totalling 249 species. Together, these data represented all 16 superfamilies and 36 families of extant Orthoptera. We included 60 transcriptomes, of which 39 orthopteran species were newly generated either by the 1K Insect Transcriptome Evolution (1KITE) consortium or by the Song Lab at Texas A&M University. The remaining 21 transcriptomes (11 orthopteran and 10 polyneopteran) were from the previous publications (see Supplementary Methods 1. 1). To increase taxon sampling, we then combined the transcriptome data with 169 previously and 80 newly generated mtgenomes from 249 taxa. RNA extraction, cDNA library preparation and transcriptome sequencing and assembly were performed within the 1KITE project using the protocols detailed in Supplementary Methods 1.
2 and 1. 5. Protocols used for the Song Lab samples, as well as for mtgenome data generation are detailed in Supplementary Methods 1. 3 and 1. 4. A detailed list of all species, including their collection data and National Center for Biotechnology Information (NCBI) accession numbers, is presented in Supplementary Data 1 and 2. For the transcriptome data, a custom-made orthologous gene set was designed with OrthoDB v7 (ref. 92 ) using four hemimetabolous (Zootermopsis nevadensis, Pediculus humanus, Acyrthosiphon pisum and Rhodnius prolixus) and one holometabolous (Nasonia vitripennis) species, which resulted in 5414 proteincoding genes. We used Orthograph v0. 5. 3 (ref. 93 ) to generate a profile hidden Markov model (pHMM) from the amino-acid sequences of each reference gene, which was used to search for ortholog candidates in transcript libraries.
Orthograph ran protein BLAST (blastp) search using the translated query protein sequences against a database of all amino-acid sequences from all the reference orthologous genes/groups (OGs). For each pHMM hit transcript, the corresponding BLAST result was checked whether the best hit sequence belonged to the OG that the pHMM is based on. Only if the sequence matched, the bestreciprocal hit criterion was fulfilled and the OG was extended with the candidate transcript. Using these methods, we identified on average 3700 OGs. The aminoacid sequences of these OGs were individually aligned on amino-acid level using MAFFT v7. 130b  94  with the L-INS-i algorithm, and the quality of the multiple sequence alignment (MSA) was checked using the pipeline described in Supplementary Methods 1. 5. For downstream phylogenetic analyses, we considered regions identified as protein clans, families, single domains or non-annotated regions as evolutionary units in the partitioned analyses.
Yeast expression plasmids. Mutations E340A D341A were introduced by GeneCust by site-directed mutagenesis of pSH63, yielding plasmid pGY372. We generated the N-terΔ21 mutant of Cre by PCR amplification of the P GAL1 promoter of pSH63 using primer 1L80 (forward) and mutagenic primer 1L71 (reverse), digestion of pSH63 by AgeI and cotransformation of this truncated plasmid and amplicon in a trp1Δ63 yeast strain for homologous recombination and plasmid rescue. We combined the N-terΔ21 and the C-ter E340A D341A mutations similarly, but with pGY372 instead of pSH63. We generated N-terΔ28 and N-terΔ37 mutants, combined or not with C-ter E340A D341A mutations, by the same procedure where we changed 1L71 by mutagenic primers 1L72 and 1L73, respectively. To generate a Cre-VVD fusion, we designed sequence CreCVII (Supplementary Text S1) where the Cre sequence from GENBANK AAG34515.
The saturated culture was transferred to two 96-well polystyrene flat-bottom Falcon ® sterile plates (100 µl per well) and one plate was illuminated at the indicated intensities while the other plate was kept in the dark. After the indicated duration of illumination, cells from the two plates were transferred to a fresh medium allowing expression of GFP but not cell division (SD-W-H or SD-W-U-H, strain GY1761 being auxotroph for histidine) and these cultures were incubated at 30°C for 90 minutes. Cells were then either analyzed immediately by flow cytometry, or blocked in PBS + 1mM sodium azide and analyzed the following day. We acquired data for 10,000 events per sample using a FACSCalibur (BD Biosciences) or a MACSQuant VYB (Miltenyi Biotech) cytometer, after adjusting the concentration of cells in PBS.
We analyzed raw data files in the R statistical environment (www. r-project. org) using custom-made scripts based on the flowCore package  70  from bioconductor (www. bioconductor. org). We gated cells automatically by computing a pGY519, yielding plasmid pGY523. Fourth, we inserted the HindIII-NotI cassette of pGY521 into the HindIII-NotI sites of pGY519, yielding plasmid pGY524. Fifth, a HindIII-BamHI fragment of pGY523 containing one terminator, and a BglII-EcoRI fragment of pGY524 containing another terminator were simultaneously cloned as consecutive inserts in the BglII-EcoRI sites of 51269. Finally, the resulting plasmid was digested with HindIII and BamHI to produce a fragment that was cloned into the HindIII-BglII sites of pGY524 to produce pGY525. To establish stable cell lines, Flp-In™ T-REx™ 293 cells were purchased from Invitrogen (ThermoFisher) and transfected with both the Flp recombinase vector (pOG44, Invitrogen) and pGY525.
Calculation of potential mean force (PMF). We calculated the free-energy profile (reported in Figure  1f ) for the unbinding of the C-terminal α-helix in the tetrameric Crerecombinase complex  26  (PDB Entry 1NZB) as follows. The software we used were: the CHARMM-GUI server  71  to generate initial input files; CHARMM version c39b1  72  to setup the structural models and subsequent umbrella sampling by molecular dynamics; WHAM, version 2. 0. 9 (http://membrane. urmc. rochester. edu/content/wham/) to extract the PMF; and VMD, version 1. 9. 2  73  to visualize structures. To achieve sufficient sampling by molecular dynamics, we worked with a structurally reduced model system. We focused thereby only on the unbinding of the C-terminal α-helix of subunit A (residues 334:340) from subunit F. Residues that did not have at least one atom within 25 Å from residues 333 to 343 of subunit A were removed including the DNA fragments.
Umbrella sampling  76  was performed with 13 independent molecular dynamics simulations where the system was restrained to different values of the reaction coordinate (equally spaced from 4 to 10 Å) using a harmonic biasing potential with a spring constant of 20 kcal mol -1 Å -1 (GEO/MMFP module of CHARMM). Note that this module uses a pre-factor of ½ for the harmonic potential (as in the case of the program WHAM). For each simulation the value of the reaction coordinate was saved at every time-step for 30 ns. After an equilibration phase of 5ns, we calculated for blocks of 5 ns the PMF and the probability distribution function along the reaction coordinate using the weighted histogram analysis method  77. A total of 13 bins were used with lower and upper boundaries at 3. 75 and 10. 25 Å, respectively, and a convergence tolerance of 0.
Bar: 10 µm. g) Quantification of intra-cellular mCherry fluorescence from (f), n = 22 cells. h) Design of qPCR assay allowing to quantify recombination efficiency. i) Quantification of excision by qPCR immediately after illumination at 3. 63 mW/cm 2 intensity (stationary phase, strain GY1761 transformed with pGY466). j) DNA excision does not occur after illumination. X-axis: same data as shown on Y-axis in (i). Y-axis: same experiment but after illumination, cells were incubated for 90 minutes in dark and non-dividing condition prior to harvest and qPCR. k) Quantification of DNA excision by qPCR on exponentiallygrowing or stationary-phase cells (strain GY1761 transformed with pGY466) illuminated at   Quantification of carotenoids production. Three colonies of strain GY2247 transformed with LiCre plasmid pGY466 were cultured overnight in SD-W-M.