dataesr/scientific-paragraphs-categorization huggingface dataset:
2009)  of the MAUVE software  (Darling et al. 2004 ). The contigs that could not be identified relative to the K279a genome sequence (one for each strain) were placed at the end of the alignment. Coding sequences (CDSs) predictions, as well as automatic and manual sequence annotations, were performed using the MicroScope platform pipeline at Genoscope  (Vallenet et al. 2013). Results are available through the MaGe graphical interface  (Vallenet et al. 2006). CDSs were predicted using AMIGene software  (Bocs et al. 2003). Automatic functional annotation of the predicted CDSs was performed using the tools integrated in the MicroScope platform  (Vallenet et al. 2009 ) and the available annotations of the strain K279a and other related genomes. Gene predicted to be involved in functions of interest was manually checked by using the "genome browser" tool of the platform.
Genomic islands and regions of genomic plasticity (RGPs) of each genome were identified using the "RGP finder" tool included in the MicroScope platform by comparing the genome of each query against all the other studied genomes as reference. The nucleotide sequences of the strains BurA1, BurE1, and PierC1 were deposited into European Nucleotide Archive (http://www. ebi. ac. uk/ena) with the accession numbers ERS685922, ERS685923, and ERS685924, respectively (the study accession is PRJEB8824).
Phylogenetic Analysis The evolutionary relationships among the 14 studied S. maltophilia strains were determined from a concatenated alignment of the orthologous protein sequences of the core genome of these 14 strains. Orthologous proteins were identified from bidirectional best hit BLASTP searches of each strain proteome against K279a's proteome with an e-value parameter threshold of 10e-5. Customized computer scripts were then used to extract the best reciprocal hits from all the strains and to align these protein sequences with Clustal omega  (Sievers et al. 2011 ). The alignments were then filtered using Gblocks version 0. 91 b  (Talavera and Castresana 2007)  with default options and concatenated. A final alignment of 1,647 concatenated proteins (514,787 amino acids) was used in the phylogenetic analyses.
Antibiotic Resistance Gene and Efflux Pumps Content Identification Antibiotic resistance genes and efflux pumps were identified by keyword searches after automatic and manual annotation of the CDS. Searches were also performed using InterPro database family identifier numbers  (Hunter et al. 2009). InterPro IDs were attributed to CDS by the InterProScan software  (Quevillon et al. 2005)  during the annotation process. Putative resistance and/or efflux functions were confirmed using BLASTP against the nonredundant protein sequence database. Known antibiotic resistance genes and efflux pumps described in S. maltophilia but not retrieved by the two previous methods were searched in the draft genomes by BLASTP searches after retrieving these sequences in the GenBanK database  (Benson et al. 2013).
General Features of the Sequenced Genomes The general genomic features of the three novel S. maltophilia environmental strains sequenced in this study are summarized in the table 3. The draft genomes of BurA1, BurE1 and PierC1 consisted of approximately  4,366,960, 4,509,290 and 4,644,375  bp circular chromosomes assembled in 64, 48, and 59 contigs of size greater than 500 bp, respectively. No plasmids were detected in the genome assemblies or by Pulse Field Gel Electrophoresis (PFGE) (data not shown). The average G+C % of BurA1 and BurE1 was 66. 6% and this of PierC1 was 66. 3%. These data are consistent with the average G+C % of the other S. maltophilia genomes (table 3). In total, 4, 132, 4, 223 and 4, 422  predicted protein-CDSs were identified in the genomes of BurA1, BurE1 and PierC1, respectively, with an average CDS length of 952-962bp and a coding.
Overview of Antibiotic Resistance Genes Antibiotic resistance genes were sought primarily in the genomes of the environmental strains sequenced in this study as well as in those of the reference strains K279a and R551-3 for  which accurate data on their drug resistance profiles were available. On the basis of the core-genome phylogenetic clustering of the sequenced strains, other publicly available sequenced strains such as Ab55555, which clustered with strains BurE1 and K279a, and strain RR10, phylogenetically close to the strain BurA1, were added in the analysis. Strains D457 and JV3 grouped together and were included in the survey. Between 50 and 56 known or putative antibiotic resistance genes and efflux pumps commonly considered to be implied in MDR phenotypes were found among the nine strains, including genes involved in resistance to beta-lactam compounds such as penicillins and carbapenems, as well as aminoglycosides and quinolones (fig.
More distant genes around the RND operon also correspond to an ICE structure (transposon plasmid and transfer genes). For the two Xanthomonas strains, the contig containing the RND operon available in GenBank is however too short to find the encoding integrase gene. As expected, a phylogenetic study of the integrase sequence from a Cronobacter strain (C. universalis NCTC9529) confirmed that it belongs to the tn4371 ICE family (supplementary fig. S2 , Supplementary Material online). However, although the two ICE bearing genes encoding a near identical RND pump in S. maltophila BurA1 and C. universalis NCTC9529 belong actually to the same family, these two genomic islands are clearly evolutionarily distant (only 21. 4% identity between the two integrase; supplementary fig. S2 , Supplementary Material online ), which was confirmed with phylogenetic studies from the other genes of the ICE (data not shown).
At the beginning of our study, two genome sequences were available, one from the clinical MDR strain K279a  (Crossman et al. 2008 ) and the other from the environmental reference endophytic strain R551-3  (Taghavi et al. 2008). Based on their exceptionally resistant or sensitive antibiotic resistance profiles, three environmental strains from the team collection were sequenced in this study. During our analysis, other genome sequences from clinical and environmental strains became available  (Allen et al. 2012; Lira et al. 2012; Song et al. 2012; Zhu et al. 2012; Sassera et al. 2013; Zhang et al. 2013 ) but unfortunately their antibiotic resistance profiles were poorly documented. In order to have the same level of data on the antibiotic resistance of the three sequenced environmental strains and the two reference strains, automated in vitro antibiotic resistance profiles were determined.
Together, the two models are not necessarily mutually exclusive and might be reconciled by a capture elongation model mediated by Ena/VASP or formins. To interrogate and illustrate the dynamic transition from lamellipodium to filopodia, we performed mathematical simulations using the cytoskeleton simulation software Cytosim  70. In the simulation, a lamellipodium-like branched network was grown by distributing the Arp2/3 complex-like nucleators within a broad, two-dimensional area (Figure  3A , top and 61). To create the variation of lengths among those actin filaments, formin-like (could also be Ena/VASPlike) entities were added to capture the barbed ends of growing actin filaments and accelerate filament elongation. The growing actin filaments then extended out of the lamellipodium network and merged into bundled filaments by fascin-like crosslinkers.
Filopodia disassembly and their fate The mechanisms by which filopodia disassemble remain to be determined. However, stationary filopodia can be disassembled into small bundles by ADF/cofilin  81. Filopodia may also develop kinks after a decrease and/or change of direction of the actin flow between the lamellipodium and lamella leading to their integration into the Simulations were performed using the Cytosim software. In the top panel, the actin network grows by branched nucleation via the Arp2/3 complex, and a proportion of actin filaments grow longer due to capture of their growing barbed ends by an elongation factor (formin/VASP, green filaments). Actin filaments contact each other by chance due to thermal fluctuations and are stabilized in bundles by crosslinkers (fascin). In the bottom panel, the presence of elongation factors in the simulation is essential for the emergence of protrusions (left), while the crosslinkers are necessary to group the protrusions into one rigid bundle (right).
(B) Transition between lamellipodium-like and stress fiber-like networks. Simulations were performed using the Cytosim software. In the top panel, a branched network is formed and moved towards friction points (mimicking focal adhesions nucleating dorsal fibers) associated with parallel filaments. In the contact zone, the action of crosslinkers and myosins induces the disassembly of the branched network leading to the formation of a contractile structure of anti-parallel filaments. This structure is further compacted by a slow vertical flow (~centripetal actin flow) until it co-aligns with the friction points to form one contractile fiber. In the bottom panel, in the absence of motors, the network has no tension and is thus highly curved and spread (left). The crosslinkers are essential to maintain the connectivity between the filaments and form a continuous actin structure (middle).
Simulations were performed using the Cytosim software. In the top panel, a branched network is formed and moved towards friction points (mimicking focal adhesions nucleating dorsal fibers) associated with parallel filaments. In the contact zone, the action of crosslinkers and myosins induces the disassembly of the branched network leading to the formation of a contractile structure of anti-parallel filaments. This structure is further compacted by a slow vertical flow (~centripetal actin flow) until it co-aligns with the friction points to form one contractile fiber. In the bottom panel, in the absence of motors, the network has no tension and is thus highly curved and spread (left). The crosslinkers are essential to maintain the connectivity between the filaments and form a continuous actin structure (middle).
Acknowledgments We thank  F. Nedelec  for providing an unpublished code used to run the simulations with Cytosim. LB is supported by  Agence Nationale de la Recherche (ANR)  grant  N° ANR-12-BSV5-0014  (Contract). HE and LG are supported by  IRTELIS  grant from  CEA. Illustrations were made by  A. Kawska  at IlluScientia. com.
Genomic Data Sets To build TE libraries, we collected genome sequences of amphioxus (Branchiostoma_floridae_v2. 0. assembly. For tetrapods (except for turtle, see above) and Ciona, we directly used premasked genomes and RepeatMasker outfiles (". out" and ". align") from RepeatMasker Genomic Datasets (http://www. repeatmasker. org/genomicDatasets/RMGenomic Datasets. html, last accessed January 30, 2015): Ciona (ci2), frog (xenTro2), American alligator (allMis0), green anole (anoCar2), zebra finch (taeGut1), chicken (galGal3), platypus (ornAna1), opossum (monDom5), mouse (mm9), and human (hg19). For premasked genomes, genome sizes correspond to the golden path available on the Ensembl server. For others, genome sizes were calculated during the masking process.
Censor  (Jurka et al. 1996)  was also used to identify the sequences. Automatic annotation was performed using the RepeatModeler software (Smit, AFA, Hubley, R. RepeatModeler software weblink: http://www. repeatmasker. org, last accessed January 30, 2015) with default parameters. For the coelacanth, we used and reannotated the library from  Amemiya et al. (2013).
Kimura Distance-Based Distribution Analysis of TE Copies in Genomes Kimura distances between genome copies and TE consensus from the library were determined using RepeatLandscape (https://github. com/caballero/RepeatLandscape, last accessed January 30, 2015) on alignments included in. align files after genome masking with RepeatMasker. The rates of transitions and transversions were calculated on alignments and transformed to Kimura distance  (Kimura 1980 ) by using the following equation: K = À1/2 ln(1 À 2p À q) -1/4 ln(1 À 2q), where q is the proportion of sites with transversions and p the proportion of sites with transitions. For tetrapods (except for turtle) and Ciona, TE landscapes are available on http:// www. repeatmasker. org/genomicDatasets/RMGenomicData sets. html (last accessed January 30, 2015).
Presence/absence of TE superfamilies was determined using automatic annotation, manual verification, and literature information. Presence of superfamilies is shown by full squares with gray gradient. Absence is represented by dashed squares. The premasked genome of the western clawed frog does not provide details within the CR1-like superfamily. Superfamilies having been domesticated at least once in the bony vertebrate lineage are shown by asterisks. Divergence times between species were estimated using the TimeTree public database  (Hedges et al. 2006 ) and literature data based on fossil records. (DNA transposons, SINE, LINE, and LTR retrotransposons)  in the different genomes analyzed, clustered according to Kimura distances to their corresponding consensus sequence (x axis, K-value from 0 to 50).
Copies clustering on the left of the graph do not diverge very much from the consensus sequence of the element and potentially correspond to recent copies, while sequences on the right might correspond to ancient/degenerated copies. For more clarity, PLE elements have been included into LINE elements and DIRS sequences into LTR retrotransposons, and subclass I and subclass II DNA transposons have been grouped. For tetrapods (except for turtle) and Ciona, TE landscapes are also available on http://www. repeatmasker. org/genomicDatasets/RMGenomicDatasets. html, last accessed January 30, 2015). Both bird species studied showed two major transposition bursts: In chicken, an initial burst involving LINE and DNA transposons was followed by a second burst of only LINEs; in the zebra finch, the oldest burst was LINE elements and the youngest burst was due to LTR retroelements.
Acknowledgments This work was supported by PhD grants from the  French Ministry for Higher Education and Research and from the "Ligue Nationale contre le Cancer"  (to D. C. ). We thank the  CBP  and PSMN centers at the  ENS Lyon , especially  Emmanuel Quemener  and  Thomas Bellembois , for technical IT supports;  Emmanuelle Lerat  and  Clement Goubert  for help and advices;  Marie Se  ´mon for helpful comments; and  Ian Warren  for careful reading of the manuscript.
73. dna. toplevel. fa, Ensembl), Atlantic cod (Gadus_ morhua. gadMor1. 73. dna. toplevel. fa, Ensembl), zebrafish (Danio_rerio. Zv9. 66. dna. toplevel. fa, Ensembl), European eel (draft genome version 1, www. zfgenomics. org/sub/eel, last accessed January 30, 2015), spotted gar assembly accession update (http://www. ncbi. nlm. nih. gov/assembly/GCF_ 000242695. 1/, last accessed January 30, 2015, Genbank Assembly), African coelacanth (Latimeria_chalumnae. LatCha1. 72. dna_toplevel. fa, Ensembl), and Chinese soft- shell turtle (Pelodiscus_sinensis. PelSin_1. 0. 73. dna. toplevel. fa, Ensembl). fasta, http://genome. jgi-psf. org/Brafl1/Brafl1. download. ftp. html, last accessed January 30, 2015), Oikopleura (Odioica_referen ce_v3. fa, http://www. genoscope. cns. fr/externe/Genome Browser/Oikopleura/, last accessed January 30, 2015), lamprey (Petromyzon_marinus.
For energy feeding systems for ruminants to evolve towards a nutrient-based system, dietary energy supply has to be determined in terms of amount and nature of nutrients. The objective of this study was to establish response equations of the net hepatic flux and net splanchnic release of acetate, butyrate and β-hydroxybutyrate to changes in diet and animal profiles. A meta-analysis was applied on published data compiled from the FLuxes of nutrients across Organs and tissues in Ruminant Animals database, which pools the results from international publications on net splanchnic nutrient fluxes measured in multi-catheterized ruminants. Prediction variables were identified from current knowledge on digestion, hepatic and other tissue metabolism. Subsequently, physiological and other, more integrative, predictors were obtained.
Selection of publications and description of the nutritional values of diets We used the FLuxes of nutrients across Organs and tissues in Ruminant Animals database  (Vernet and Ortigues-Marty, 2006)  which includes ~250 international publications. To be eligible, publications had to report the net hepatic fluxes and the net splanchnic release of acetate, butyrate and β-hydroxybutyrate (see Figure  1  for definitions) and no exogenous treatments or infusions had to be applied. For each nutrient, and in the same respective order, a total of 25, 22, 24 publications (corresponding to 61, 59, 58 dietary treatments) were eligible and selected for the present work (Supplementary Table S1 lists all the selected references). In all studies from this data set, different dietary compositions or amounts were tested with frequent meal distributions for the nutrient supply and animal metabolism to be at steady state.
Given that choice of matrix has no impact on β-hydroxybutyrate  (Nozière et al. , 1998)  or butyrate net fluxes  (Reynolds and Huntington, 1988)  and presents only a small underestimation of net portal appearance of acetate when measured in plasma (by 7%,  Nozière et al. , 1998) , no attempt was made to homogenize data and correct plasma into blood concentrations and fluxes. Moreover, the analytical methods for measuring β-hydroxybutyrate (β-hydroxybutyrate-dehydrogenase plus hydrazine) and volatile fatty acids (extraction by ion exchange resin in all but one Loncke, Nozière, Bahloul, Vernet, Lapierre, Sauvant and Ortigues-Marty publication) were similar between publications. Finally, splanchnic blood flows were measured using the paraaminohippuric acid down-stream dilution method. Eighty per cent of the publications did not correct for the incomplete recovery of para-aminohippuric acid across the liver, demonstrated in sheep by  Katz and Bergman (1969)  and in cows by Rodriguez-Lopez et al.
(2014). To evaluate the potential impact of this methodological error, it was specifically compared whether correction of net hepatic fluxes and net splanchnic release data for incomplete marker recovery modified the prediction equations. We recalculated net fluxes assuming that the hepatic arterial blood/plasma flow represented 10% of hepatic venous blood/plasma flow as measured when paraaminohippuric acid is de-acetylated before analysis (Rodriguez- Lopez et al. , 2014). This correction could only be applied when publications reported blood flow and nutrient concentration data in addition to net fluxes. It was the case in 61%, 59% and 76% of the publications used in the models of acetate, butyrate and β-hydroxybutyrate, respectively. Potential predictors of variation in nutrient net hepatic flux and net splanchnic release Potential predictors of the net hepatic fluxes of nutrients were identified from current knowledge on hepatic metabolism.
All of the data (nutrient intake, net portal appearance, and net hepatic and splanchnic fluxes) were initially expressed as a function of BW 1. 0 to ensure normal distribution of the variables across species  (Loncke et al. , 2009). Selection and coding of studies. In order to select relevant studies for subsequent meta-analyses, the full set of selected publications was coded in several steps (Vernet et al. , 2005;  Sauvant et al. , 2008), considering first the experiments, and second the groups of treatments that changed due to only one factor, defined as studies within a given experiment. Studies were coded for variations in the proportions of forage to concentrate, intake level, forage type, CP or starch content of the diet, physiological state, which are known to affect the selected predictors.
The residual mean square error (RMSE) was considered low when lower than 10% of the mean value of the predicted variable. This defined the good fit of the model. External evaluation. A limited external evaluation was carried out in order to check the absence of systematic bias or slope rotation. In addition to publications selected to establish the within-study models, the other data initially excluded from the selected data set (see above) but reporting the net hepatic fluxes and net splanchnic release of acetate, butyrate and β-hydroxybutyrate were used. The prediction models obtained were evaluated by comparing the observed (Y) and the predicted net hepatic fluxes or net splanchnic release (X), using a GLM model including a study effect. The model was considered unbiased when the intercept was not different from 0 and when the slope was not significantly different from one.
Critical evaluation of the estimated dietary and animal characteristics To critically evaluate the estimated animal EB, we used the publications that reported EB data measured in respiratory chambers. Data were only available in growing and finishing steers and all reported positive EB. The expected EB (calculated as indicated in Table  1 ) was compared with the retained energy reported in the publications. Although only five studies (10 treatments) could be used, the estimated EB Intakes of these components were therefore different between species. These differences were reflected in the nutrient concentrations and fluxes. However, the widest differences in diet intake and composition were recorded among physiological status rather than among species. Although physiological status was partly confounded with species and feeding conditions, it best discriminated the different animal profiles (Table  4 ).
The majority of data was obtained on non-productive adults, followed by growing, lactating and gestating dry animals. All gestating animals were in late gestation (⩽2 months before calving). Concerning lactation, only dairy cattle were represented; they were between 11 and 240 days in milk (12 treatments for the first 80 days in milk and eight treatments for 120 to 240 days in milk). Lactating cows had the highest DM intake levels and received diets with the highest proportions of concentrate, the highest digestibility and the highest concentrations of starch and ME (Table  4 ). Based on descriptive statistics, the net hepatic fluxes of acetate, butyrate and β-hydroxybutyrate averaged 0. 233 ± 0. 0572, -0. 111 ± 0. 0749 and 6. 48 ± 4. 70 mmol/kg BW per hour, respectively across the full data set.
, 1987). This effect had not been detected with the descriptive statistics probably because the defined animal classes (imposed by the available data) were insufficient to discriminate between early-and late-lactating cows, or fed and fasted non-productive animals, as reflected by the high standard deviation. To evaluate the relevance of our GLM models for predictive purposes beyond this range of validity, we compared them with models established with the Mixed procedure of SAS considering random the study effect (Supplementary material S2). Models were not significantly different, except for the prediction of net hepatic fluxes of β-hydroxybutyrate which proved more reliable with the GLM procedure. Prediction of the net hepatic fluxes of acetate Present work addresses both the quantitative importance of the net hepatic flux and the response of this flux to changes in input.