dataesr/scientific-paragraphs-categorization huggingface dataset:
The applied method followed the technique described in  Wang et al. ( 2017 Wang et al. ( , 2018a , b ) , b ). The calculation of an upper mass limit was performed numerically via direct orbit integrations of the equations of motion. For this task, we modified the FORTRAN -based MICROFARM 10  package  (Go ździewski 2003 ; Go ździewski, Breiter & Borczyk 2008 )  which relies on OPENMPI 11 to spawn several parallel tasks. The package's main purpose is the numerical computation of the Mean Exponential Growth factor of Nearby Orbits (MEGNO;  Cincotta & Sim ó 2000 ; Go ździewski et al. 2001 ; Cincotta, Giordano & Sim ó 2003 )  o v er a grid of initial conditions of orbital parameters. In this work, we followed a direct brute-force method for the calculation of the RMS statistic. We integrated the orbit of HATS-18 within the framework of the general three-body problem.
2001 ; Hinse et al. 2010  ). In addition to the Newtonian equations of motion, the associated variational equations are solved simultaneously at each integration time-step. The MICROFARM package implements the ODEX 12  extrapolation algorithm to numerically solve the system of first-order differential equations. This algorithm is slow but robust even for high-eccentricity orbits as well as close encounters. When presenting results (Fig. 5  ) we al w ays plot the time-averaged MEGNO that is utilized to quantitatively differentiate between quasi-periodic and chaotic dynamics. We refer to  Hinse et al. ( 2010 )  for a short re vie w of the essential properties of MEGNO. In a dynamical system that evolves quasi-periodically in time the quantity Y will asymptotically approach 2. 0 for t → ∞. In that case, the orbital elements associated with that orbit are often bounded.
AC K N OW L E D G E M E N T S We thank Dr. Kaloyan Penev and Dr. Joel Hartman for their help in tracking down the issue with the LCOGT transit timing. AJB was supported by STFC grants ST/S000275/1 and ST/W000873/1. UGJ acknowledges funding from the Novo Nordisk Foundation Interdisciplinary Synergy Programme grant no. NNF19OC0057374 and from the European Union H2020-MSCA- The following internet-based resources were used in research for this paper: the ESO Digitized Sky Survey; the NASA Astrophysics Data System; the SIMBAD database operated at CDS, Strasbourg, France; and the ar χ iv scientific paper preprint service operated by Cornell University. This work is based on data collected by MiNDSTEp with the Danish 1. 54 m telescope at the ESO La Silla Observatory.
Europlanet 2024 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 871149. This research received financial support from the National Research Foundation (NRF; No. 2019R1I1A1A01059609). The following internet-based resources were used in research for this paper: the ESO Digitized Sky Survey; the NASA Astrophysics Data System; the SIMBAD database operated at CDS, Strasbourg, France; and the ar χ iv scientific paper preprint service operated by Cornell University. This work is based on data collected by MiNDSTEp with the Danish 1. 54 m telescope at the ESO La Silla Observatory.
Quantitative PCR For qPCR, 1 µL of cDNA was amplified with the Taqman Universal Mastermix II (Life Technologies) in a 10 µL total reaction volume; 5 µL of the Mastermix, 1. 5 µL of CDNA, and 3. 5µL of assay mix were included in the reaction. The primers were bought from Applied Biosciences. The TaqMan assays were performed using a 79,000 HT Fast Real-Time system (AB). For data analysis, the mouse Eef1alpha, β-actin, Gapdh, and Tbp housekeeping genes were used as internal controls. Gene expression profiling was achieved using the Comparative CT method (DDCT) of relative quantification  [21]  using the SDS 2. 4 software (Applied Biosystems, Waltham, United States).
Interspecies Sequence Comparison The comparison of the conserved noncoding elements and deletions in mouse-rat, mouse-guinea pig, mouse-squirrel, mouse-rabbit, mouse-human, mouse-chimp, mouse-gorilla, mouse-orangutan, mouse-rhesus, mouse-dolphin, mouse-cow, mouse-cat, mouse-dog, mousehorse, mouse-elephant was performed using the Vertebrate Multiz Alignment and Conservation Track in the UCSC genome browser, using a window size of 2 kb. HiC data on topological associated domains (TADs) from ES cells were obtained from http://3dgenome. fsm. northwestern. edu/view. php (accessed on 11 April 2020)  [22, 23].
Normalization was performed by dividing the fragment scores by the mean of fragments scores falling into a region defined as +/-1 Mb around the center of the bait coordinates. Smoothed signals were obtained by applying a running mean algorithm with a window size of eleven fragments. The profile corrected data were generated by applying an approach similar to the one described in  [26]  using a fit with a slope -1 in a log-log scale  [27]. The 4C-Seq data are deposited in GEO under the accession number GSE193356 (Table  5 ).
Statistical Analysis To compare the contacts between the Lef1 promoter and Leaf, in the E12. 5 whisker pad and the adult kidney, we considered the normalized and profile corrected fragments from region chr3:131 008 663-131 026 430 for Leaf viewpoint, and those from region chr3:131106987-131227057 for Lef1 promoter. Statistical differences were assessed by applying an unpaired non-parametric two-tailed Mann-Whitney test after having excluded the normality of the data with a D'Agostino and Pearson omnibus normality test. Differences were considered significant if the p-value, p, was less than 0. 05 and shown in figures as * (* p < 0. 05, ** p < 0. 01, *** p < 0. 001, **** p ≤ 0. 001). For Leaf, fragments of region Chr3:131008663-131026430 (mm10) were analyzed whereas, for the Lef1 promoter and coding sequence, the fragments of region Chr3:131106987-131227057 were analyzed.
Identification of Regulatory Elements Lost during Evolution in Whisker Morphogenesis To understand if the de-regulation of Prdm1 and/or Lef1 might help to explain vibrissae reduction and their eventual loss in humans, we looked at their regulatory regions. As for Lef1, a transposable enhancer trap mapping to a particular locus (chr3:130,927,182-130,927,529 in mm10 assembly) suggests that its regulatory region is located on the centromeric side of the gene in the adjacent gene desert (TRACER LacZ expression database, SB line name 183038-emb20)  [40]. The transgene expression can be observed at E11. 5 in the brain, mammary glands, whisker pad, and the tip of tail, tissues/organs where Lef1 is physiologically expressed during development (Figure  6A ). We next compared the multispecies alignment of animals with and without whiskers in the aforementioned locus, searching for putative regulatory elements.
We found high statistical significance between the scores mapping Leaf in the E12. 5 whisker pad compared to the adult kidney in both normalized and profile corrected datasets (****, Mann-Whitney test, p = 0. 0008 in normalized and p < 0. 0001 in PC). In the reciprocal experiment, we scored the contacts from the murine Leaf enhancer with the promoter and coding sequence of Lef1. Similarly, we showed a high statistical significance between the scores mapping Lef1 in the E12. 5 whisker pad compared to the adult kidney (****, Mann-Whitney test, p < 0. 0001 in normalized and p < 0. 0001 in PC), suggesting productive long-range interactions between Leaf and Lef1 in the whisker pad, confirming our observations from the specular viewpoint. To validate Leaf as an enhancer, we then performed CUT&Tag  [42]  on E12 wild-type whisker pads to map the presence of monomethylation of histone 3 lysine 4 (H3K4me1)-a post-translational modification enriched at active and poised enhancers.
Acknowledgments: We are grateful to  Michiko Kanemitsu  for kindly providing us with the results for Figure 4 and Figure  S4. We thank  Mitinori Saitou  and  Azim Surani  for providing the Prdm1mEGFP mice,  Rudolf Grosscheldl  and  Werner Held  for providing the Lef1tm1Rug mice,  Irene Pizzitola  for breeding and mating Lef1tm1Rug mice,  Denis Duboule  for support, discussions, and suggestions on the evolutionary part of the paper, the  EPFL CPG  ( Emilie Gesina ,  Gisele Ferrand ) and the animal house of  Epalinges (Francis Derouet, Lisa Arlandi ) for mice handling,  Orbicia Riccio ,  Elisabeth Joye  and  Severine Urfer  for sharing probes for in situ hybridization,  Olga de Sousa Silva  and  Lai Quiewen  for technical help.
They are traditionally referred to as humic-like components  40. Component C2 autoDOM (Ex/Em: 240(300)/342) had a fluorescence signal which is similar to free and protein-bound amino acids and has been ascribed to autochthonous DOM  45. Components C4 (Ex/Em: 230/306) and C5 (Ex/Em: 230(275)/340) were similar to tyrosine-like and tryptophan-like compounds. 45 All optical analyses including PARAFAC were conducted using the software R (v4. 0. 2. ) in Rstudio  46  with the package staRdom ("spectroscopic analysis of DOM in R"). 47 All corrected EEMs of seawater in the POS533 cruise (n = 299) were used for modeling. The identified fluorescent components were compared with the published data on an open-access spectral database  48  (OpenFluor, https://openfluor. lablicate. com). The database compares fluorescence data sets and determines Tucker congruence (set at 95%) as the similarity criteria between pairs of excitation and emission spectra.
IMPORTANCE Streptomyces rimosus is best known as a primary source of oxytetracycline (OTC). The significant global market value of OTC highlights the need for a better understanding of the regulatory mechanisms that lead to production of this antibiotic. Our study provides, for the first time, a detailed insight into the dynamics of (phospho)proteomic profiles during growth and antibiotic production in liquid culture of S. rimosus. Significant changes in protein synthesis and phosphorylation have been revealed for a number of important cellular proteins during the growth stages that coincide with OTC production and morphological changes of this industrially important bacterium. Most of these proteins have not been detected in previous studies. Therefore, our results significantly expand the insight into phosphorylation events associated with important cellular processes and antibiotic production; they also greatly increase the phosphoproteome of streptomycetes and contribute with newly discovered phosphoproteins to the database of prokaryotic phosphoproteomes.
Its draft genome sequence was completed in 2013  (24)  and recently resequenced by Pacific Biosciences (PacBio) (GenBank accession number CP048261). The S. rimosus genome is 9. 64 Mb (including a 0. 29 Mb giant linear plasmid), which is within the range of other published streptomycete genome sequences. Recently, an uncommon set of telomeres of the linear S. rimosus G7 chromosome has been revealed  (25). The genome is estimated to have a total of 8,166 protein-coding genes (263 encoded by the plasmid). Among the protein-coding genes, 32 are predicted to be serine/threonine protein kinases (STPKs). A previous study confirmed protein tyrosine phosphorylation in the S. rimosus wild-type strain  (26). Here, we determined the dynamics of (phospho)proteome profiles in S. rimosus during three very distinct stages of bacterial growth.
rimosus at three specific stages of growth, described above. We performed stable isotope dimethyl labeling of peptides obtained from proteins at the three different stages of growth. Mass spectrometry (MS) measurements identified 200,982 MS/MS spectra corresponding to 33,023 peptides and 3,725 protein groups (45. 6% of the theoretical S. rimosus proteome) (see sheet 1 of Data Set S1 in the supplemental material). This was in agreement with a previous analysis of S. coelicolor grown on solid medium  (17). To evaluate reproducibility between the two biological replicates, we calculated the correlation coefficients for each protein ratio. SIII/SII and SIII/SI showed a high correlation between replicates (0. 82 and 0. 84, respectively), whereas the correlation for SII/SI was somewhat lower (0.
Our major goal was to investigate whether there were any functional subcategories/categories among the identified proteins that were prevalent in the phosphoproteome in relation to the proteome. Functional annotation of all identified (phospho) proteins was performed using eggNOG-mapper (Data Set S1; sheets 1 and 2). Their distribution into 20 functional subcategories is shown in Fig. 2 , while distribution in major categories is shown in Fig. S1. The most prevalent category in both the proteome and phosphoproteome was "metabolism" (40% and 35%, respectively), followed by "unknown" (23% and 27%, respectively). Although proteins with unknown function remain to be investigated, their abundance suggests important biological roles at various stages of bacterial growth, while their presence in the phosphoproteome suggests that their function may be regulated by phosphorylation.
(ii) Phosphoproteome dynamics. As for the proteome, we examined the dynamics of protein phosphorylation during the SI, SII, and SIII growth stages. Out of 417 phosphorylation sites identified in this study (Data Set S1, sheet 2), 191 were quantified in at least one replicate (Data Set S1, sheet 5). To identify phosphorylation sites with changes in abundance, we defined an arbitrary threshold of a 3-fold change (1. 5 on a log 2 scale) for phosphorylation site ratios. With this approach, we identified 71 proteins exhibiting 98 differentially regulated phosphorylation sites (Data Set S1, sheet 5). Among them, 55 proteins had only one, while 16 proteins had multiple upregulated phosphorylation sites. These phosphoproteins, grouped into six major functional categories as described in Materials and Methods, were divided between growth phases in accordance with the upregulation of their phosphorylation site(s) (Data Set S1, sheet 6).
We compared S. rimosus and S. coelicolor phosphoproteomes using Diamond software  (53)  and found only 47 phosphorylated orthologs, while 28 additional were found in the dbPSP  (54). Altogether, of S. rimosus 230 phosphoproteins, 155 (67%) were not found among previously reported S. coelicolor phosphoproteins. The majority of these proteins belong to the categories "metabolism" and "unknown," suggesting that phosphoproteomes in bacteria are still very much understudied. In addition, we provide information for those found to be differentially phosphorylated (Fig. 5D ), which can help in future research by elucidation of their biological role during very specific growth phases. Subsequently, we aligned 47 phosphoproteins of S. rimosus with their matching S. coelicolor orthologs obtained by Diamond software.
e. , mostly in Actinobacteria (Table  S5B ). Considering the potential of Actinobacteria to produce antibiotics and other bioactive compounds, phosphorylated orthologs specific to this phylum could be important for production of secondary metabolites and morphological differentiation. Finally, our study contributes 55 phosphorylated proteins to the database of prokaryotic phosphoproteomes that have not been previously reported (Table  S5A ). Almost half of these were distributed among "information storage and processes" (1), "cellular processes and signaling" (6), and "metabolism" (9), while 39 remain uncharacterized (Fig. 7 ; Fig. S6 ). Eleven of these 55 phosphoproteins exhibited increased phosphorylation at specific growth phases, and the most interesting ones that well represent the physiological state of the bacterium have been described in previous paragraphs (Fig.
The chromatographic data were analyzed using EZChrom Elite software (Agilent Technologies, Germany). The concentration of glucose in samples was determined by ultraperformance liquid chromatography (UPLC) using the Agilent Technologies 1290 Infinity II LC system (Santa Clara, CA, USA) with a Carbo-H 11 precolumn (4 mm by 3 mm; Phenomenex, Des Plaines, IL, USA), a Rezex ROA column (15 cm by 7. 8 mm; Phenomenex), and a refractive index detector. The mobile phase was 0. 0025 M H 2 SO 4 , the volume of the analyzed sample was 10 mL, and the flow rate was 0. 6 mL/min. The temperature of the column was 60°C. The results were analyzed with OpenLab CDS software. Fluorescence microscopy. S. rimosus G7 spores were inoculated into a 100 mL Erlenmeyer flask containing 10 mL seed medium as described, and the culture was shaken at 250 rpm at 30°C.
A few experiments were measured on an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific) with previously described parameters  (63). Raw data processing. Acquired raw data were processed using the MaxQuant software suite version 2. 0. 3. 0  (69). MaxQuant-generated peak lists were searched using the Andromeda search engine (70) against the proteome of S. rimosus G7 genome (GenBank accession number CP048261), as well as the associated plasmid (GenBank accession number CP048262). Carbamidomethylation of cysteines was set as a fixed modification, while methionine oxidation, protein N-terminal acetylation, and Ser/Thr/Tyr phosphorylation were defined as variable modifications. Trypsin was chosen as a protease with up to two missed cleavages, and the minimum required peptide length was set to seven amino acids.
The mass tolerance window for parent and fragment ion isolation was set at 4. 5 ppm and 20 ppm, respectively. A false-discovery rate (FDR) of 1% was set at the peptide, protein, and phosphorylation site levels  (71). Statistical analyses. Significance analyses of differentially regulated proteins and phosphorylation events were performed with Perseus software (version 1. 6. 14. 0. ). All contaminants, reverse hits, and proteins identified only by the modification site were removed. For quantitative proteome analyses, data were filtered to have at least one measured ratio in both replicates. Significantly regulated proteins were identified by one sample t test with a P value of 0. 05 and an s 0 parameter of 0. 1. For the phosphoproteome analyses, phosphorylation site ratios were normalized to their respective abundances of protein groups, transformed to log 2 , and plotted against the respective log 10 -transformed phosphorylation site intensities  (72).
An arbitrary threshold of 1. 5 on a log 2 scale (3-fold change) was used for the assignment of differentially regulated phosphorylation sites to certain developmental stages (if the phosphorylation site was quantified in all three stages). Clustering analysis. Proteins with similar temporal abundances were clustered using hierarchical clustering analysis. This analysis was performed using Perseus on significantly regulated proteins obtained by t test (P , 0. 05). Proteins were normalized using Z-score and clustered based on calculation of Euclidean distance. Functional annotation and functional enrichment analysis. The proteins were functionally annotated with gene ontology (GO) biological processes (GOBP), molecular functions (GOMF), cellular compartments (GOCC), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein families (PFAM), and enzyme commission (EC) functional resources and added to Perseus software.
These annotations were obtained by performing protein sequence orthologous assignment with the evolutionary genealogy of genes: nonsupervised orthologous groups (eggNOG-mapper) software  (73). Proteins with differentially regulated phosphorylation sites were grouped into six major functional categories according to their biological roles, as the number of phosphoproteins per 20 subcategories defined by eggNOG was relatively small. Clusters were tested for enrichment based on the mentioned annotation terms by using Fisher's exact test. Annotation terms with adjusted P values below 0. 05 in any of the clusters and with an enrichment factor above 1 were considered significant. Phylogenetic analysis. Predicted Ser/Thr kinases (STPKs) from the S. rimosus G7 strain (32 sequences) and 25 out of 27 STPKs of S.
coelicolor M415 identified by other proteomics studies  (15, 16)  were used to perform multiple-sequence alignment (MSA) with the PROMALS3D tool  (74). Two kinases were removed, SCO3360, which was annotated as a hypothetical protein which shared similarity to aminoglycoside 39-phosphotransferase, and SCO3941, which was biochemically characterized as a protein phosphatase with dual-substrate specificity  (75). Two STPKs with solved three-dimensional structures from Mycobacterium tuberculosis (PDB IDs 6I2P and 3OUV) were used to improve alignment quality. A phylogenetic tree of aligned kinase sequences was constructed using the maximum-likelihood method in PhyML  (76). Approximate likelihood ratio test (aLRT) values were used to infer branch support. Branches with aLRT values greater than 0.
9 were considered well supported. Analysis of phospho-orthologs in prokaryotes. To identify S. rimosus phospho-orthologs in other prokaryotes, we used the dbPSP 2. 0 database (http://dbpsp. biocuckoo. cn). It comprises 19,296 experimentally identified phosphorylation sites in 8,586 proteins from 200 microorganisms that belong to 12 phyla within domains of Bacteria and Archaea.
ACKNOWLEDGMENTS We thank  Marin Roje  and  Mladenka Jurin  for the measurement of OTC in culture media,  Božidar Šantek  and  Marina Grubi  c for the measurement of glucose consumption, and  Ivo Crnolatac  for valuable discussion. This work was supported by the  Unity through Knowledge Fund  ( UKF grant   27/15  to D. V. ). B. M. was supported by grants from the  Deutsche Forschungsgemeinschaft (German Research Foundation Cluster of Excellence EXC 2124 ,  SFB 766 ,  FOR 2816 ,  TRR 261 ; project  ID   398967434 ), the  European Union 's  Horizon 2020 Research and Innovation Program  under the  Marie Sklodowska-Curie  grant agreement  955626 , and the  German-Israeli Foundation  grant  I-1464-416. 13/2018. E. Š. was supported by the  UKF  fund and by the  Croatian Government  and the  EU  through the  ERDF's Competitiveness and Cohesion Operational Program  ( KK.
WNV MNT performed on horse samples at ANSES in the frame of interlaboratory proficiency testing generated comparable results (data not shown). Briefly, serial dilutions of Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 2% foetal bovine serum were mixed with USUV and WNV suspension at 100 tissue culture infectious dose 50 (TCID50). After incubation for 90 min at 37°C allowing for viral neutralisation, 100 µL containing 2,000 Vero cells (human samples) or 2x104 Vero cells (horse samples) were mixed in each well and plates were incubated for 3 to 5 days at 37°C. The presence or absence of a cytopathic effect was determined and compared with controls. A titre was determined for each sample from the reciprocal of each dilution. The tests were performed twice in two independent experiments.
For USUV sequencing, we performed a PCR with the primers 4723fwd (5'-GTCATGTATGAAGGRGTT-3') and 5672rev (5'-GTGTAYTCTGTTATCCACTC-3'). The primers target a region of the NS3 gene (their 5' position is indicated in the name). Sequences of WNV were obtained using a PCR which targets a part of the NS5 gene as previously described to discriminate WNV lineages  [31]. The GenBank accession numbers of the USUV sequences are ON125263, ON099437, ON099438, ON099439, and ON099436 for WNV sequence.
Phylogenetic analyses Phylogenetic analyses were performed in Geneious (Dotmatics). Multiple alignments were generated with the default Geneious algorithm. All positions containing gaps and missing data were not included. The alignment for USUV included 33 partial sequences from mosquitoes of the NS3 gene (682 bp, positions 4,736-5,614). The alignment for WNV included 51 partial sequences (all from mosquitoes, except one from a horse) of the NS5 gene (1,000 bp, positions 9,039-10,039). Trees were generated with the Tree Builder A titre was determined for each sample from the reciprocal of each dilution. function using the maximum likelihood approach and the Jukes-Cantor model.