dataesr/scientific-paragraphs-categorization huggingface dataset:
RESULTS EFT41964 (mmdH) is required for the catabolism of linear ␣-1,4-linked maltodextrins. The genes mmgT to GenBank accession no. EFT41964 of E. faecalis JH2-2 are located upstream from an operon which encodes an ABC transporter catalyzing the uptake of maltotetraose and longer maltooligosaccharides (Fig. 1 )  (9). Genes with sequences nearly identical to those of mmgT to EFT41964 are found in all E. faecalis strains for which the genome has been sequenced, and they are usually annotated as ␣-amylase genes. We therefore suspected that they might play a role in maltodextrin metabolism. Compared to growth on glucose and maltose, the wild-type strain grew similarly well on maltotriose but significantly slower on maltotetraose (Fig. 2A ) and still slower on longer maltooligosaccharides and maltodextrin (data not shown).
this unexpected result, we carried out a coupled two-step spectrophotometric assay. An increase in OD 340 and therefore glucose oxidation occurred during both steps, similar to that shown in Fig. 4. MmdH must therefore release maltose from the nonreducing end of isopanose and thus function as a maltose-producing ␣-1,6 maltodextrin hydrolase (Fig. 5 ). The V max of the hydrolysis of isopanose was about 6-fold slower (13 mol • min Ϫ1 • mg of protein Ϫ1 ) and the K m 2-fold higher (5. 9 mM) than the values determined for maltotriose, which is probably partly responsible for the slightly slower growth of E. faecalis on isopanose than on maltotriose (compare Fig. 2A  and 6 ). A spectrophotometric assay revealed that MmdH also hydrolyzes maltotriose-6Љ-P, the product formed during the PTS-catalyzed transport of the triose, to glucose and probably maltose-6=-P (data not shown).
7 ), although E. faecalis cannot grow on these two compounds. The release of glucose from isomaltose and isomaltotriose by the enzyme GmdH was also confirmed by carrying out the glucose dehydrogenase-coupled spectrophotometric assay (data not shown). The formation of glucose from isomaltotriose was found to be 2. 5 times faster than that from isomaltose. In contrast, GmdH was not able to detectably hydrolyze pullulan, a polysaccharide in which maltotriose units are connected via ␣-1,6 linkages (data not shown). EFT41962 (MmgT) functions as maltooligosaccharide:maltooligosaccharide glucosyl transferase. We also inactivated the third gene in the amylase operon but could not attribute a physiological role to the encoded protein, which is also annotated as ␣-amylase. The resulting mutant grew identically to the wild-type strain on all maltooligosaccharides tested (data not shown).
7 ). Again, no glucose could be detected among the reaction products. In order to confirm the observed combined ␣-1,4-glucosidase and glucosyltransferase activities of MmgT, we also carried out two-step spectrophotometric assays coupled to glucose dehydrogenase and either maltose phosphorylase or MmdH. When MmgT was incubated with maltotriose, no increase in the OD 340 occurred, confirming that the enzyme does not liberate glucose from the trisaccharide. However, when maltose phosphorylase was also present in the assay mixture, the OD 340 increased, confirming that MmgT liberates maltose from maltotriose and transfers the remaining glucose to another maltotriose molecule. When we carried out spectrophotometric assays with maltotetraose, again, MmgT did not release a detectable amount of glucose from the tetrasaccharide (data not shown).
1 mM isopropyl-␤-D-thiogalactopyranoside (IPTG). The cells were harvested by centrifugation, and the preparation of crude extracts and purification of the His-tagged proteins on nickel-nitrilotriacetic acid (Ni-NTA) columns under nondenaturing conditions were carried out as described in reference 34. b ϩ, oriented in the direction of transcription; Ϫ, oriented opposite of the direction of transcription. Maltose phosphorylase of E. faecalis strain JH2-2 is encoded by the gene with GenBank accession no. EFT41759. The His-tagged enzyme was overexpressed in E. coli from the expression vector pQE30 and purified as previously described  (8). In vitro maltooligosaccharide hydrolysis and thin-layer chromatography. In order to determine the enzymatic activities of the three purified enzymes (MmdH, GmdH, and MmgT), which are all annotated as ␣-glucosidases, 10 l of a solution of various maltooligosaccharides (10 g/ml) in 50 mM Tris-HCl (pH 7.
ACKNOWLEDGMENTS This research was supported by grants from the  MinCyt/ECOS-Sud program  (action no. A09B03 ) (C. M. , A. H. , and J. D), the  Agencia Nacional de Promoción y Tecnológica (AN-PCyT , contracts  2014-1513  [to C. M. ] and  2014-3482 [V. S. B. ] Argentina ), the " Initiative d'Excellence" program  from the  French government  (grant  DYNAMO ,  ANR-11-LABX-0011 ) (to J. D. ), and by a chair of excellence at the  University of Caen  for C. M. financed by the  Region of Normandy  and the  European Regional Development Fund (ERDF). A. M. received a fellowship from the  Algerian government , and V. S. B. , M. E. , and C. M. are Career Investigators of  CONICET (Argentina). We thank  Maria Fernandez  for sending plasmid pAGEnt and  John Thompson  and  Andreas Pikis  for providing maltotriose-6Љ-P.
The location of the 3d metal doping cation was also systematically identified for both HAp and β-TCP phases. Rietveld refinements were performed using the FullProf. 2k program  [37]. The procedure used (both data collection and refinement strategy) corresponds to the general guidelines for structure refinement using the Rietveld (whole-profile) method formulated by the International Union of Crystallography Commission on Powder Diffraction  [38, 39]. The Rietveld strategy was detailed in a previous related work  [14] ; the quality of refinements has been assessed using standard procedures and all reliability factors were below 5%.
0 × 10 -4 , necessary to resolve the XANES structure. The experiments were calibrated with metallic reference foils (K-edge 9659 eV for zinc, K-edge 8981 eV for copper, K-edge 8332 eV for nickel, K-edge 7709 eV for cobalt, and K-edge 7109 eV for iron). Experiments were performed at room temperature and atmospheric pressure. Spectra were collected in an energy range of 1000 eV, with energy steps varying from 0. 5 eV (XANES part) to 2. 0 eV (end of the EXAFS part) and 1 s dwell time per point. XAS spectra were obtained in fluorescence mode using Ge-solid-state detectors (13-element detector). The beam size was determined by a set of slits (200 µm × 500 µm). Data were processed using the Athena and Artemis programs from the IFFEFIT software package  [40]  by merging six successively recorded absorption spectra.
Post processing of imaging data According to  [14] , we performed post processing steps with free-software platforms. In medical image processing, segmentation means selection of voxels on slices in order to gather them in region of interest (ROI) representing an anatomical or pathological entity. We performed segmentation of skull base and sinuses bone with Medical Image Segmentation Tool (MIST, freeware, available on https://github. com/BenjaminGilles/MIST) on CT and μCT imaging to get 3D objects (Fig  3 ). Mucosa, nerves, vessels and other soft tissues were excluded from the segmentation. ROI were segmented using a combination of semi-automatic intensity thresholding (beyond 300 Hounsfield Units), region growing and slice-by-slice manual contouring in orthogonal triplanar view. For thin lamellar bone, an automatic segmentation process based on region growing was corrected after by an expert with manual interaction.
Acknowledgments The authors would like to gratefully acknowledge the technical support of  Mr Olivier Tempier  from the robotic division of the LIRMM, and all the neuroradiology team of the university hospital of Montpellier. Data used in this work were (partly) produced through the technical facilities of the  MRI platform and of the labEx CeMEB. This work was supported by the  Languedoc-Roussillon Regional Health Agency.
1H fosmid DNA sequence. The in silico analysis of the 42,318 bp environmental DNA revealed that it contained 46 open reading frames (ORF) in both orientations (Fig. 3 ). The analysis of the G + C content with GC-Profile highlighted a global G + C of 45. 6 mol % (100 bp window), with three segments (1-8,963 bp: 49 mol %; 8,926-21,987 bp: 37. 7% and 21,958-42,318 bp: 49. 1 mol %) (Fig. 3 ). Besides these variations of the G + C content, a detailed analysis of the sequence revealed that the codon usage of most of the amino acids detected was equally distributed among their different forms. Comparison of the deduced protein sequences against the protein sequences available in the GenBank sequence database revealed that 31 out of 46 ORFs showed a high sequence homology with the class Deltaproteobacteria and among them, 25 ORFs equally distributed in the fosmid insert were related to sulphate-reducing bacteria (SRB) proteins (Table  1 ).
Moreover, HqiA shows the conserved catalytic domains (D, K and C) of the CSHase family and presents a very different three-dimensional structure than the other AHL lactonases based on a Phyre2 analysis  30  (see Supplementary Fig. S1 ). hqiA encodes for an AHL lactonase. To identify the function of the HqiA protein, hqiA was sub-cloned in the expression plasmid pMAL-c2TEV under the control of a Lac promotor to generate the fusion protein MBP-HqiA. The TEV protease-processed recombinant protein revealed a molecular weight of about 26 kD (see Supplementary Fig. S2 ). AHL-degrading activity of hqiA was confirmed against all the AHLs using a crude extract of induced E. coli carrying pMAL-c2TEV-ORF29, whilst no AHL degradation occurred with E. coli carrying the empty vector (data not shown). Furthermore, as revealed with biosensors, the degradation assays performed with the purified recombinant HqiA protein confirmed the AHL-degradation activity associated with the HqiA peptide (Fig.
5 ). To assign the enzymatic activity of the HqiA protein, the product of the enzymatic reaction between the purified recombinant protein and C 12 -HSL was identified by using both the lactone ring closure assay and HPLC/MS. Thus, after acidification of the supernatant with HCl and neutralisation of the pH, the C 12 -HSL-related signal was significantly recovered as evidenced using the A. tumefaciens biosensor (see Supplementary Fig. S3 ). Similar results were obtained with other AHLs (data not shown). The analysis by HPLC/MS of the main peak obtained after the C 12 -HSL degradation assay (HqiA) revealed a mass (M-) of 300, which corresponds to the open-ring form of the C 12 -HSL, while in the chromatogram corresponding to the control (RE) a molecular weight of 282, compatible with the closed form, was detected (Fig.
Until very recently, most of our knowledge on QS and QQ relied only upon cultivation-based approaches, ignoring a large part of the microbial diversity and the functional potential of the bacterial communities occurring in complex and extreme environments  37, 38. The first cultivation-dependent study focusing on the relative distribution of the bacteria from the soil capable of producing or degrading AHLs showed that 8-19% of these bacteria had the capability to produce AHLs, whilst 2-3% had the capability to degrade AHLs  39. The proportion of potential AHL-producing bacteria was shown to reach 13% when considering the proteobacterial genomes available in the international sequence database NCBI, but these genes appeared far less frequently in non-proteobacterial genomes  40. The metagenomic approaches based on shotgun sequencing or fosmid libraries gave very different pictures.
The run of pyrosequencing yielded 50,457 reads. These sequences were used to generate a de novo assembly with the Roche 454 sequencing assembly software Newbler. This assembly resulted in one contig of 50,457 bp, corresponding to 8,139 bp of the pCC1FOS fosmid and to 42,318 bp of metagenomic insert. ORFs in this insert were predicted by using the RAST and GeneMark applications  78, 79. After gene prediction, nucleotide and aminoacid sequence analyses were made using BLAST  80. G + C content was calculated using the web tool GC-Profile  81. For each protein encoded by the fosmid f1017. 1H, homologous protein sequences were retrieved from NCBI after identification by BLAST X  80. Multiple sequence alignments and phylogenetic trees were constructed using Seaview  82. Briefly, alignments were carried out with ClustalO  83.
Protein concentration was assayed using the Bradford method  86. The potential three-dimensional structure of the purified protein was calculated using the software Phyre2, a web portal for protein modeling, prediction and analysis based on aminoacid sequences  30. Characterization of the AHL-degrading activity of purified HqiA. AHL-degradation activity of the purified HqiA was tested in reaction buffer (RE) (200 mM Na phosphate, pH 6. 5) containing 16 µg ml -1 of HqiA protein and 25 µM of each of the synthetic AHLs. After incubation at 28 °C for 4 h, the remaining AHLs were detected on agar plates overlaid with A. tumefaciens NTL4 (pZLR4) as previously described above. To identify the type of QQ enzyme, the degradation products of the QQ reaction of HqiA were analyzed by HPLC/MS and by the lactone ring closure assay after acidification  72, 74.
Acknowledgements This research was supported by grants from the  Dirección General de Investigación Científica y Técnica  ( CGL2011-25748 ,  BIO2011-12879E ,  AGL2015-68806-R ) and from  INRA  (MetaScreen, Projet innovant and the  Labex ARBRE   ANR-11-LABX-0002-01 ). Marta Torres  is supported by a  FPU fellowship  from the  Spanish Ministry of Science and Education  ( FPU13-0466 ) and a  University of Granada-CEI BioTic International Mobility Programme. The authors thank  Angela Tate  for her critical reading of this manuscript,  Nahid Oueriaghli  for supplying the soil samples, the  Functional Ecogenomics  platform for their services and  Pr. John S. Parkinson  ( University of Utah, USA ) for providing the E. coli RP437 strain and its related chemotaxis mutants.
Search for Conserved Domains and Homologs To identify homologs of experimentally identified proteins we ran a BLAST 2. 2. 30+  (Camacho et al. , 2009)  search against two local databases. The first contains a selection of 255 representative Firmicutes and the second contains all 112 currently available Negativicutes genomes. Default settings were used except for an E-value cutoff of 0. 0001. Protein domains were searched using the conserved domain database (CDD) from NCBI  (Marchler-Bauer et al. , 2014) , PFAM  (Finn et al. , 2015) , InterPro  (Finn et al. , 2017) , and PANTHER 10. 0  (Mi et al. , 2015)  with the required Evalue cutoff of 0. 00001. Protein folds were predicted with Phyre2  (Kelley et al. , 2015).
Mass Spectrometry Analysis Trypsin-digested peptides coming from gel samples were analyzed by nano LC-MS/MS using an Ultimate 3000 system (Dionex, Amsterdam, The Netherlands) coupled to an LTQ-Orbitrap Velos. File microliters of each sample were loaded on a C 18 pre-column (300 µm inner diameter × 5 mm; Dionex) at 30 µL/min in 2% ACN, 0. 1% FA. After 5 min of desalting, the pre-column was switched online an in-house packed 15 cm nano-HPLC column (75 µm inner diameter) with C 18 resin (3 µm particles, 100 Å pore size, ReproSil-Pur Basic C 18 , Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) and equilibrated in 95% solvent A (2% ACN, 0. 1% FA) and 5% solvent B (80% ACN, 0. 08% FA). The peptides were eluted using a 2-50% gradient of solvent B during 60 min at 300 nL/min flow rate. The LTQ-Orbitrap Velos (Thermo Fisher Scientific, Bremen) was operated in data-dependent acquisition mode with the XCalibur software (Thermo Fisher Scientific, Bremen).
Maisch GmbH, Ammerbuch-Entringen, Germany) and equilibrated in 98% solvent A (H 2 O, 0. 1% FA) and 2% solvent B (ACN, 0. 1% FA). Peptides were eluted using a 2-45% gradient of solvent B during 120 or 240 min at 250 nL/min flow rate. The instrument method for the Q Exactive Plus was set up in the data dependent acquisition mode using XCalibur 2. 2 software (Thermo Fisher Scientific, Bremen). After a survey scan in the Orbitrap (resolution 70,000 at m/z 400), the 10 most intense precursor ions were selected for higher-energy collision dissociation (HCD) fragmentation with a normalized collision energy set to 28. Charge state screening was enabled, and precursors with unknown charge state or a charge state of 1 and >7 were excluded. Dynamic exclusion was enabled for 35 s. In order to increase throughput and sensitivity methods used to acquire the data with these two mass spectrometer have been optimized in accordance with recommended settings from Thermo Fisher Scientific using HeLa extract sample (from Thermo) and an in-house complex quality control sample.
Data Processing and Analysis Raw data were searched using MaxQuant (version 1. 4. 1. 2)  (Cox and Mann, 2008; Cox et al. , 2014;  with the Andromeda search engine) against V. parvula Uniprot database  (1,844 entries, version 10-2015)  and concatenated with known MS contaminants and reversed sequences of all entries. Andromeda searches were performed choosing trypsin as specific enzyme with a maximum number of two missed cleavages. Possible modifications included carbamidomethylation (Cys, fixed), oxidation (Met, variable), and Nter acetylation (variable). Maximum peptide charge was set to seven and five amino acids were required as minimum peptide length. Most peptides (∼89%) were identified with charge states < +3. Less than 10% of peptides were identified with a charge state > +4. As you may see on the graph, peptides (∼0.
Protein identifications were filtered, removing hits to the reverse decoy database as well as proteins only identified by modified peptides or considered as potential contaminant. Protein LFQ intensities were logarithmized. Two valid values out of three were required for each protein for the confident quantification across all replicates and missing values imputed by values simulating low abundance values close to the noise level. For pairwise comparison and identification of enriched proteins, a modified t-test were applied with permutation-based FDR statistics set to 1% and a S 0 of 1  (Tusher et al. , 2001). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  (Vizcaíno et al. , 2016)  partner repository with the dataset identifier PXD005929.
The 23 proteins robustly predicted to be in the OM include many known OM components such as TonB-dependent receptors, OmpM, components of the BAM/TAM machinery, TolC, and OmpA (Table  S1 ). Although localization prediction methods were able to identify these OM components, they have limitations due to training on datasets of known OM proteins, most of which are from the phylogenetically distant Proteobacteria. This could prevent proper prediction of many proteins and fail to find novel OM proteins. Indeed, they failed to correctly identify the experimentally characterized trimeric autotransporters, which were predicted as secreted or had undefined localization (Table  S1 ). As such, we more thoroughly investigated the 297 proteins with undefined prediction or predicted as secreted, as they might contain additional OM proteins.
As shown in Figure  1B , to do so, we constructed a bioinformatic filter to sort these 297 proteins. Briefly, we identified the proteins that contained a signal sequence for translocating through the IM, by checking for the three IM transport mechanisms: SEC, ESP (Extended signal peptide), and TAT with seven different programs (Figure  1B ; see Section Materials and Methods). Hundred and ninety-one proteins lacked any recognizable signal sequence and were excluded. The remaining 106, which included all of the previously missed trimeric autotransporters, were combined with the 23 predicted OM proteins to provide a final dataset of 129 potential outer membrane proteins (Table  S2 ).
In order to reduce false positives from this dataset, we crossed it with the 129 potential OM proteins obtained by our bioinformatics prediction (Table  S2 ). This led to a final list of 78 OM proteins (Table  1  and Table S3 ) that we annotated and created a graphical schematic representation in a V. parvula cell as shown in Figure  3. Identification of these OM proteins markedly extends previous inferences on the nature of the cell envelope of Negativicutes  (Antunes et al. , 2016 ) and provides information on the role of OM systems in the lifestyle of Veillonella. Additionally, among the 1,844 predicted proteins of V. parvula roughly one quarter of them (502) were not expressed in our growth conditions or were not detected by MS due to their low concentration. As an example, we previously detected a conserved genomic locus coding for all components of a Type 4 pilus (T4P), including an OM secretin  (Antunes et al.
However, this fails to account for the strong OM prediction of TamB by localization software PSORT, CELLO, and SOSUI (Table  S1 ), which indicates that some OM characteristics must be present within the V. parvula TamB; unfortunately we cannot determine what these characteristics are, due to the machine learning nature of the programs. Interestingly, TamB of E. coli (NP_418642. 1) is also predicted to be in the OM by two out of the three programs (not shown), yet its IM/periplasmic localization has been firmly established through protease shaving  (Selkrig et al. , 2012). Discrepancies also exist in previous fractionation mass-spectrometry studies, as TamB was found in higher concentration in the OM than in the IM in E. coli  (Martorana et al. , 2014). Together, these data suggest that TamB may actually be both in the OM and the IM, or span the two membranes.
In addition, vpar_0646 and lptD are FIGURE 4 | Distribution of selected protein-coding genes in select proteins among Negativicutes. Schematic tree based on phylogeny of the Negativicutes from previous analysis  (Antunes et al. , 2016). Presence and absence of key genes are indicated by + andsymbols, respectively. The dominant niche of each strain taken from the available literature is also given. For discussion, see main text. conserved in sequence and synteny among all Negativicutes members (Table  S3 ). We were unable to ascertain the function of Vpar_0645 & 0646 as we could find no conserved domains or clear homologs in sequence databases. It is possible that these proteins function with the Lpt complex of V. parvula or are functional equivalents of LptE, which caps the transport pore of LptD.
Finally, we detected the periplasmic components LptA (Vpar_0548) and LptC (Vpar_0547) in our OM and surfaceexposed fractions. LptC was excluded from our final OM dataset because it did not pass the bioinformatics filter due to a lack of any discernible signal sequence. While we cannot exclude a contamination of periplasmic components in our OM fraction, it is possible that LptA and LptC were dragged to the OM fraction by strong interaction with LptD, thereby suggesting the existence of a complete Lpt complex in V. parvula similar to other studied bacteria  (Villa et al. , 2013).
Lipoproteins Lipoproteins are found in most diderm bacteria and can be targeted to the outer membrane by the LOL transport machinery  (Sutcliffe, 2010; Dowdell et al. , 2017). We previously noted the absence of any LOL transport components (lolA-E) in any Negativicute genome  (Antunes et al. , 2016) , however we find that 17 out of 78 OM proteins contain a lipoprotein signal sequence as predicted by LipoP and PRED-LIPO software (Table  1  and Table   S3 ). To resolve this incongruence, we further analyzed the MS data of OM proteins that contained a cysteine residue. We searched for any mono, di, or triacylglycerol with a saturated C16 or C18 fatty acid as a modification (Data not shown). No such modification was found on any of the proteins, supporting the hypothesis that Veillonella does not have OMtargeted lipoproteins.