dataesr/scientific-paragraphs-categorization huggingface dataset:
Switch from monovalent to bivalent N-glycan binding With the crystal structure available for an N-glycan binding bivalently to FimH, a structural and functional analysis in order to decipher the driving forces favoring bivalent versus monovalent N-glycan binding becomes imminent. We compared the two new crystal structures with crystal structures of FimH in complex with Man3Gn2 (PDB entry 2VCO) and with Man3 (PDB entry 6GTV), in terms of their proteincarbohydrate interactions (Table  S4 ). We computed the free energy of binding, ΔG, for each of the different glycans, using a hybrid MM-PBSA approach (Table  S3 ), identical to what had been performed for the dimannoside glycans. MD simulations were performed with oligomannosides of growing complexity, using either the crystal structure of the complex or docking (Table  S3 ).
These simulations clearly highlight that Manα1,3Man at the nonreducing end is always preferred over any other glycan arm, which agrees with the observations for the dimannoside series (Table  S2 ). Interestingly, the difference in free energy of binding between the two binding nonreducing mannose ends A and B is relatively smaller for those glycan structures containing the second trimannose core (A-4 0 -B) (Table  S3 ). In the crystal structure of donor-strand complemented, two-domain adhesin, FimH with trimannose (Man3) (PDB entry 6GTV), the bivalently bound trimannose is positioned in the same way as its moiety in Man6Gn2 N-glycan, however it is enrobed inside a hollow cylinder pulled up by the tyrosine gate (48 and 137) and isoleucine (13 and 52) residues from the two interfacing FimH monosaccharide(M)-binding pockets (PDB entry 6GTW)  (18).
The chitobiose moiety of Man6Gn2 requires the hollow cylindrical interface to open at the reducing end (the central mannose) of Man3, in order to disengage the Tyr48 side chains that are essential for stacking interactions beyond M + 1 in the FimH-Man6Gn2 complex (Fig. 7  and Table  S4 ). This opening up is already visible in the FimH-Man3 crystal structure containing only the lectin domain (PDB entry 6GTW). Perhaps the most striking observation is the impossibility of oligomannose-6 to bind where Tyr48 is in an open-gate conformation: the central α-mannose 4 0 and the central β-mannose 3 notably travel through the same space (Fig. 8A ). Binding of the Manα1,6Manβ1 of Man3Gn2 would cause a   S8 ). As Tyr48A takes on the closed gate conformation to allow the passage of mannose 4 0 , it loses the carbohydrate ring-aromatic Figure  6.
Bivalent binding of FimH adhesin by oligomannose-6 in the crystal structure (PDB entry 7QUO). A, SNFG symbols, nomenclature, and linkage description of the oligomannose-6 N-glycan, here named Man6Gn2. B, a space-filling model allows a lateral look on the asymmetric plug-in of the A and B mannoses in the monosaccharide-binding pocket of two FimH lectin domains. The cyan spheres represent nickel ions, that were included at 10 mM in the crystallization condition. C, the averaged structure derived upon MD simulations illustrates a stable bivalent assembly. The cartoon is colored by the temperature (B-)factor, varying from blue (cold) over green, yellow, and orange to red (hot). MD, molecular dynamics; SNFG, Symbol Nomenclature for Glycans. The ABC of oligomannose-6 binding to FimH ring stacking typifying the binding of β-mannose 3 in Man3Gn2 (21) (Fig.
8 ). It remains to be seen whether this may possibly provoke altered cell signaling, for example upon E. coli type-1 fimbrial adhesion  (27). The second FimH lectin binds Manα1,6Manα (B-4 0 ) in the same site that had been occupied by the chitobiose (2-1) in the monovalent complex. When comparing to Man3Gn2F1  [6] , mannose B comes in nearly the same place as alternate conformation B of fucose, being the position of the core fucose that is conserved between the two Man3Gn1F1  [6]  protein chains (Fig. 8B ). Mannose 4 0 is less interactive (Table  S4 ), as it mainly plays the role of the hinge between the two monosaccharide-binding pockets occupied by mannoses A and B, respectively. In this way, suppleness is permitted in the relative orientations of the bridged FimH lectin domains, a characteristic that has also been observed earlier in the crystals of FimH-trimannose (Man3) complexes (PDB entries 6GTV and 6GTW (  18 )).
Completing this glycan branch with another mannose, α1,2-linked to mannose C, or identical to isomer 7D1 (one of the Man7Gn2 isomers), might potentially increase the likelihood of a trivalent binding. A similar case is found for a lectin from the cyanobacterium Nostoc ellipsosporum. Cyanovirin-N binds Man6Gn2 using the third epitope for FimH and achieves nanomolar affinity for Man9Gn2 upon completion of the branch with another α1,2-linked mannose D1  (29). In the bivalent assembly of FimH with oligomannose-6, the nonreducing mannoses A and B of Man6Gn2 are linked with the central mannose 4 0 , via an α1,3 and an α1,6 glycosidic bond respectively, to form a second trimannose core, A-4 0 -B (Fig. 6A ). It was not previously noted that the central mannose of Man3 (Manα1,3(Manα1,6)Manα/β1) spontaneously adopts the α-anomeric configuration in its bivalent complex with FimH (PDB entries 6GTW for the lectin domain only and 6GTV for the donor-strand complemented full-length FimH)  (18).
Man3 makes similar interactions in the monosaccharidebinding pocket M of FimH, with mannose 4 0 in the M + 1 site forming a hinge between the mannoses A and B (Table  S4 ). In other words, the trimannose (A-4 0 -B) structure is present both in Man6Gn2 and Man3 that share this same binding epitope for FimH. It differs from the common trimannose core (4-3-4 0 ) in that the central, reducing mannose is restricted to an α-anomeric configuration, instead of a β-anomeric configuration. Interestingly, in the complex of Man3 bivalently bound to the Burkholderia cenocepacia soluble lectin BC2L-A, only the α-anomeric configuration of the central mannose was retained (PDB entry 2WRA)  (30). Therefore, it is identical to the second trimannose core, A-4 0 -B, of N-glycans. Man3 binds bidirectionally to BC2L-A, where each binding site holds 50% of mannoside A and 50% of mannoside B.
Unfortunately, oligomannose-6 was not available for printing on the array. Nevertheless, we can observe that FimH largely disregards the α1,6-linked mannose when it is the sole mannose at the nonreducing end of a paucimannose or hybrid-type structure (Figs. 1  and S2A ). The recognition by FimH improves when a second α1,6-linked mannose is present as a part of the second trimannose core (A-4 0 -B), in the sequence Manα1,6Ma-nα1,6Manβ1. Such a linear sequence is present in Man6Gn2 and in Man5Gn2. Man5Gn2 bound to human THGP was recently shown in a monovalent complex with FimH, in a structure obtained by cryo-CM (PDB entry 7Q3N  (33) ). The same high-affinity epitope as in Man3Gn2, Manα1,3-Manβ1GlcNAcβ1,4GlcNAcβ1, was recognized, again illustrating that the presence of the second trimannose core in Man5Gn2 on its own is not sufficient to make the switch to bivalent binding.
01% Tween-20). The polyclonal anti-FimH antibody solution (1: 1000 dilution, 200 μl) was incubated on the microarrays for 1 h at RT. The slides were washed with PBST. Next, they were incubated with Alexa Fluor 555 Goat Anti-rabbit IgG(1:1000) (Thermo Fischer Scientific) in PBS (1% BSA, 0. 01% Tween-20) for 1 h in the dark. The microarrays were washed to remove unbound antibody with PBST, PBS and water, and subsequently dried in a slide spinner. The fluorescence measurements were performed on Agilent G2565BA Microarray Scanner (Agilent Technologies) at 10 μm resolution. The quantification of fluorescence was carried out using ProScanArray Express software (PerkinElmer; https://www. perkinelmer. com/uk/lab-products-and-services/resources/ software-downloads. html) employing an adaptive circle quantification method from 50 μm (minimum spot diameter) to 300 μm (maximum spot diameter).
Average relative fluorescence units values with local background subtraction of four spots and SD of the mean were reported using Microsoft Excel and GraphPad Prism software (https://www. graphpad. com/ features). Maximum intensity relative fluorescence units normalization was applied and is presented in Figure  1. Crystallization and data collection on FimH-Man3Gn2F1  [6]  FimH lectin domain was concentrated to 17 mg/ml, equal to 1 mM of protein, and mixed with 1 mM of M3Gn2F1  [6]. The cocrystallization was set up at 20 C using the sitting-drop vapor diffusion method. Crystals appeared in 1. 1 M Li 2 SO 4 , 0. 1 M Tris-HCl at pH = 9. 0, 0. 01 M NiCl 2 , and 3% glycerol. Data were collected at beamline Proxima-1 of the Synchrotron Soleil in Saint-Aubin, France. The crystals diffracted to 1.
4 Å resolution. PDB entry 2VCO  (21)  was used as a model, upon removal of the N-glycan ligand Man3Gn2 and water molecules, to resolve the crystal structure using molecular replacement using PHASER  (38). Crystallographic refinement was performed using phenix. refine (39)  from the Phenix package  (40)  and the refined model was manually adjusted using the graphics program Coot (41-43) (Table  S1 ). Model refinement was finalized using Refmac5 (44) and the N-glycan ligands have been validated using Privateer (45). These steps have been repeated using data that were rescaled and remerged using Staraniso  (46, 47) , in order to account for anisotropy in the diffraction data (Table  S1 ).
Crystallization and data collection on FimH-Man6Gn2 FimH lectin was concentrated to 13. 6 mg/ml (0. 8 mM) and mixed with 1 mM of the Man6Gn2. The The ABC of oligomannose-6 binding to FimH cocrystallization was set up at 18 C using the hanging drop vapor diffusion method. Crystals appeared in 1. 0 M Li 2 SO 4 , 0. 1 M Tris-HCl at pH = 8. 5, 0. 01 M NiCl 2 , and 3% glycerol. Data were collected to 3. 0 Ǻ resolution at beamline P14 of the Synchrotron Petra III in Hamburg, Germany, in a serial crystallography approach upon locating five crystals grown onto the surface of a large salt crystal (Fig. S6 ) using a grid scan  (48, 49). Molecular replacement was performed using FimH with PDB code 5FX3  (25). The structure was refined using Phenix  (40)  and finalized using Refmac5  (44). The glycan structure torsion library was corrected (50) and validated using Privateer  (45).
Induced-fit docking of the oligomannosides Different dimannosides and oligomannosides were docked into the FimH-binding site using the GOLD software (The Cambridge Crystallographic Data Centre; https://www. ccdc. cam. ac. uk/solutions/software/gold/). The six carbon atoms of the mannose ring of the ligand HM found in the coordinate file (PDB entry 4BUQ (51)) were used as a scaffold in the active site. A single internal structural water (below the axial O 2 hydroxyl group of the mannose ring of Man3Gn2) in the active site was treated explicitly. The FimH lectin domain cocrystallized with Man3Gn2 (PDB entry 2VCO (  21 )) was used as the starting point protein conformation. The side chains of ten residues interacting with the mannose of HM in the binding site: Ile13, Asn46, Tyr48, Asp54, Arg98, Gln133, Tyr137, Asn135, Asn138, and Asp140 were allowed to adopt different conformations during the induced-fit procedure.
The Manα1,2Man and the Manα1,3Man dimannoside conformations were retrieved from the PDB database when in complex with the P. angolensis lectin (52); (Manα1,2Man: PDB ID 1Q8O Manα1,3Man: PDB ID: 1Q8P) (Table  S2 ). The oligomannose-3 and oligomannose-6 conformations were taken from current work (Table  S3 ). All other ligand structures were generated using the online carbohydrate builder of Glycam  (53). For each ligand, ten docking poses that were energetically reasonable were kept while searching for the correct binding mode of the ligand. The decision to keep a trial pose was based on the computed energy for the interaction of the ligand with receptor of that pose. The ChemPLP fitness scoring function is the default in GOLD version 5. 2 used to rank poses. Discovery Studio Visualizer 4. 1 (Accelrys) was used for viewing.
MD simulations and free energy calculations MD trajectories were generated in the isothermal-isobaric ensemble at 300 K with the program NAMD2. 12 using the CHARMM36 force field (54). Long-range electrostatic interactions were calculated using the particle-mesh Ewald method  (55). A smoothing function was applied to truncate short-range electrostatic interactions. The Verlet-I/r-RESPA multiple time-step propagator was used to integrate the equation of motions using a time step of 2 and 4 fs for shortand long-range forces, respectively. All bonds involving hydrogen atoms were constrained using the Rattle algorithm. All systems (FimH-oligomannose complexes) were solvated and the ionic concentration was set to 0. 15 M NaCl. All ionizable groups were assigned their standard protonation state as predicted by propKa  (56).
8 μM, 0. 16 μM, 0. 032 μM) at a flow rate of 30 μl/min in 20 mM Hepes pH 7. 4, 150 mM NaCl and 0,005% Tween and at 298 K. Full regeneration of the sensor chip was not possible and a new sensor chip was prepared for at least one repetition. The data analysis was performed using the BIAevaluation software. SPR measurements of FimH binding with Man3Gn2 and Man3Gn2F1  [6]  To obtain the affinity between FimH and the glycan structures Man3Gn2 or Man3Gn2F1  [6] , SPR measurements were used on a Biacore3000 (Cytiva). The sugar Man3Gn2 and Man3Gn2F1  [6]  were immobilised respectively in flow cells 2 and 4 on a CM5 sensor chip. Flow cells 1 and 3 were left untreated and served as a reference. The binding interactions were studied at a 2-fold dilution series of FimH (8. 58 μM, 4. 29 μM, 2. 15 μM, 1.
07 μM, 0. 57 μM; 0. 26 μM; 0. 13 μM), in the running buffer containing 20 mM Hepes, 150 mM NaCl, and 0. 005% Tween at a flow rate of 30 μl min -1 and at 298 K. Regeneration performed using 50 mM NaOH allowed repeats on the same sensor chip. The data analysis was performed using the BIAevaluation software.
Acknowledgments-This work was funded in part through contract n 200445 from the  Agence Nationale de la Recherche (ANR) , on project " E-click:" Electrochemically  promoted tyrosine-click chemistry. The authors acknowledge financial support through the  Programme for EArly-stage Researchers in Lille (PEARL) , under the auspices of the  European Union   Horizon 2020 research and innovation programme, projects "ATACA" and "FimH-Mech " with  Marie Sklodowska-Curie  agreements No. 847568  and No. 750280. PEARL is coordinated by the  Foundation I-SITE ULNE  and implemented at the  Centre National de la Recherche Scientific (CNRS). We gratefully acknowledge the use of PROXIMA-1 and PROXIMA-2a beamlines at the  SOLEIL synchrotron (Saint-Aubin, France ) and of beamlines P13 and P14 at the  PETRA III storage ring  ( DESY, Hamburg, Germany ).
Data availability PDB https://doi. org/10. 2210/pdb7BHD/pdb: FimH in complex with alpha1,6 core-fucosylated oligomannose-3, crystallized in the trigonal space group, and entry https://doi. org/1 0. 2210/pdb8BXY/pdb (STARANISO data processing). PDB https://doi. org/10. 2210/pdb7QUO/pdb: FimH lectin domain in complex with oligomannose-6, and entry https://doi. org/10. 2210/pdb8BY3/pdb (STARANISO data processing). All other data are available in the article, other raw data files are available through the authors.
Immunofluorescence staining Confluent pMBMEC monolayers were stained as described before  45. Primary and secondary antibodies are listed in Supplementary Table  1. The assessment of apoptosis in pMBMECs was performed by immunofluorescence staining with the Image-iT™ LIVE Red Poly Caspases Detection Kit (Thermo Fisher Scientific, Massachusetts, USA) according to the manufacturer's protocol. As a positive control, apoptosis of pMBMECs was induced by incubation with staurosporine (1 μM; Abcam, Cambridge, UK). Images were acquired using a Nikon Eclipse E600 microscope connected to a Nikon Digital Camera DXM1200F with the Nikon NIS-Elements BR3. 10 software (Nikon, Egg, Switzerland) or an LSM 800 (Carl Zeiss, Oberkochen, Germany) confocal microscope. Images were processed by using ImageJ software (ImageJ software, National Institute of Health, Bethesda, USA) and mounted in Adobe Illustrator software.
Flow cytometry Cell surface molecules of T cells and DCs were stained with appropriate combinations of fluorophore-conjugated mAbs at saturating concentrations on ice in the dark for 30 min. Intracellular staining of T cells was performed exactly as described before  61. The antibodies used and the working concentrations are listed in Supplementary Table  1. The data was acquired using an Attune NxT flow cytometer (ThermoFisher Scientific, Massachusetts, USA) and analyzed using FlowJo 10 software.
Images were acquired at 10x or 20x magnification with an inverted microscope (AxioObserver, Carl Zeiss, Oberkochen, Germany) with phase-contrast and fluorescence illumination, every 10 s. Image analysis was performed using ImageJ software (ImageJ software, National Institute of Health, Bethesda, USA). Thirty seconds after the onset of the enhanced shear, the number of arrested T cells were counted manually by using ImageJ. The post-arrest behavior of T cells was defined and visualized as fractions of categorized T cells set to 100%, as follows: T cells that actively sent protrusions underneath the endothelium in a stationary position (probing); polarized T cells that continuously crawled on the endothelium (crawling); T cells that transmigrated across the endothelium following probing or crawling (probing + diapedesis, crawling + diapedesis); T cells that did not complete a diapedesis event with prior probing or crawling (probing + partial diapedesis and crawling + partial diapedesis); T cells that detached during the observation time (detaching).
Acknowledgements We thank to  Dr. Gaby Enzmann  her support with the biosafety level 2 work. Additional thanks go to  Charaf Benarafa  ( IVI, Mittelhäusern, Switzerland ) for providing the Granzyme B -/-C57BL/6 mice and to  Thomas Hünig  ( Institute of Virology and Immunobiology, Würzburg, Germany ) for providing the ODC-OVA C56BL/J mice. This study was funded by grants from  Swiss National Science Foundation  (grant numbers  31003A_149420  and  310030_189080 ) to  BE, Fondation Pour L'Aide a la Recherche sur la Sclérose en Plaques (ARSEP)  to BE and RL,  Fondation pour la Recherche Médicale  to RL,  Swiss National Science Foundation  (grant numbers  310030B_201271  and  310030_185321 ) to DM,  European Research Council  grant to DM,  National Institutes of Health  (grant numbers  R01 NS103212  and  RF1 NS122174 ) to AAJ.
Thus, further work is needed to understand the relationship between SOC and biodiversity to manage fire for nature-based solutions. Along those lines, our dataset has large gaps in Europe and Asia, which have unique biogeographic assemblages of plants and differences in fire behaviour, which should be addressed in future studies to test the generality of our findings. However, our dataset does cover the bioclimatic conditions and soil properties representative of the area over which we are making predictions. Although statistical upscaling provides a benchmark for evaluating the spatial distribution of SOC changes and the general order of magnitude, improving the process-based models should be a priority. Paths forward include simulating potential direct effects of fire on SOC, which may be minimal in some systems with limited organic horizons but become more important in forests.
Meanwhile, savannah-grasslands have lower per area SOC stocks, but given their large spatial extent and frequent burning, SOC stocks underlying savannah-grasslands that burn equate to ~14. 5 PgC (ref. 4). Our sink estimate is small relative to the residual land C sink (3. 1 ± 0. 6 PgC yr -1 ) (ref. 45), but given we observed continued declines in SOC with the long duration of experiments in our dataset (~60 years), SOC in drylands probably have a relatively long-lasting capacity to sequester carbon.
Study compilation and overview Our methods were similar to previous meta-analyses of how fire affects soils by calculating a response ratio of soil carbon (C) in plots with different fire treatments within sites and then comparing responses across sites  10. To obtain data from the literature, we searched for studies that measured the response of mineral soils to repeated burning (completed in May 2020) on Google Scholar. We included 'decadal', 'fire frequency', 'soils', 'repeated burning', 'carbon', 'long-term' to isolate papers with long-term repeated burning manipulations; searches were conducted in English and yielded 156 articles. We used a threshold of plots experiencing at least two fires that had been running for a decade or longer. We made one exception for a site that had been running for nine years because it was in an ecosystem that was not well represented in the dataset.
We focused on the mineral soil because of our focus on understanding fire effects in drylands, where it dominates soil C storage pools. We analysed data from the uppermost soil layers ( < 20 cm depth) because these are the most biologically active and likely to be the most responsive to burning. There is evidence that fire can alter soil C > 20 cm deep in some ecosystems  8, 10, 46  , suggesting our estimates could be conservative. The majority of our sites were from fire-manipulation experiments where fire treatments were prescribed (43 out of 53). The fire frequencies ranged from one fire every 17 years to one fire every year. The low fire treatments were usually complete fire exclusion. In some cases the authors note an incidental fire that burned through one of the fire exclusion plots, but these fires were mostly rare.
We assume that there were no overarching biases in the land use history of the experiment that would drive our trends. Herbivory was clearly biased, however, with the African savannah sites exposed to browsing and grazing. We assume that these characteristics are important natural processes in the ecosystem ( just as intermittent drought in many ecosystems) and thus included the sites in our analysis. In addition to the literature search, we incorporated data from our own surveys of seven sites. Several of these sites replace previous measurements because we wanted to extend the timescale over which fire had been manipulated (for example, in some cases plots had been surveyed in the 1990s and we re-surveyed them).
Different sites and calculations from a previous meta-analysis and field surveys Matopos studies: weighted the soil C under grasses vs trees by the tree cover. Texture data are in refs. 47,48. Kruger: we used data from our own re-survey across all the plots in 2015. Morton, Hitchiti, Cedar Creek: re-analysed the soil samples in our lab. Cedar Creek duration extended. Limestone and Chimney Springs: surveyed soils with our own sampling to extend the dataset by two decades. University Missouri: added data from Pellegrini et al. 2021  16. Wet Peachester: now from refs. 49 because this extended the dataset.
Climate variables We used WorldClim 32 to obtain climate variables for each site. In our model selection, we focused on variables related to growing season length and variability and water availability. Specifically, we analysed mean annual temperature, annual temperature range, mean precipitation (mean annual and broken down into the wettest and driest quarters) and precipitation seasonality (coefficient of variation of precipitation calculated with the standard deviation across months within a year divided by the annual precipitation and multiplied by 100). To integrate water and evaporative demand, we used an Aridity Index  51. Aridity was calculated from the WorldClim data based on data from 1950-2000. The aridity index is given as: Aridity Index = (mean annual precipitation) / (mean annual potential evapotranspiration) Potential evapotranspiration was calculated via the Hargreaves equation  52  (mm per month) using the WorldClim data as input: PET = 0.