dataesr/scientific-paragraphs-categorization huggingface dataset:
Our estimates indicate that the total BC emissions from Siberian fires in the period considered are strongly underestimated in the GFED4 inventory (by more than a factor of 2), in which these emissions are estimated at about 198 Gg. Taking into account that GFED is widely used as a "reference" database for estimations of atmospheric and climatic effects of open biomass burning, we believe that this is a significant finding. The relative difference between our monthly BC emission estimates and the corresponding GFED4 data is largest in September, exceeding a factor of 8; it is also large (a factor of 3) in May. In contrast, the BC emissions in Table  3. Optimal estimates of the BC and OC mass (in Gg) emitted from fires in the study region for individual months of 2012 and for the whole period considered (1 May-30 September).
Note that the spatial distribution of our emission data is insufficient to enable us to distinguish between agricultural and grassland fires. However, according to the GFED4 inventory, agricultural burns strongly dominate over grass fires both in May and September (by a factor of 5 at least). It is noteworthy that our estimates of the BC/OC emission ratios (in the range from 0. 036 to 0. 042 g g -1 ) for the summer months are only insignificantly -taking the confidence intervals into account -different from the EC/OC ratio of 0. 038 g g -1 that was derived for BB aerosol by  Mikhailov et al. (2017)  from aerosol measurements at ZOTTO in summer. Furthermore, our estimate for May (0. 093 ± 0. 03 g g -1 ) is in a good agreement with the EC/OC ratio (0. 08 ± 0. 02 g g -1 ) found by  Mikhailov et al.
The total BC emission estimates for each case and the relative differences with respect to the base case estimate reported in Table  3  are also listed in Table  4. Test case no. 1 addresses systematic differences between the photochemical ages of BB aerosol observed at the AERONET sites that provided the data considered in our analysis (see  Sect. 2. 1. 4 ) and those of BB aerosol observed by satellites. Figure  15  shows the histograms of the photochemical ages estimated in accordance with Eq. (  1 ) for the respective AERONET and satellite data from the datasets selected for our analysis. Compared to BB aerosol observed from satellites (which have a median photochemical age of 15. 4 h), the BB aerosol at the AERONET sites was typically more aged (with a median photochemical age of 25. 8 h).
If the relationship given by Eq. (  4 ) is sensitive to the photochemical age of the aerosol, these differences could result in some bias in the modeled AAOD values. To get an idea about the significance of such bias, we disregarded satellite data corresponding to photochemical ages smaller than 11 h. The remaining satellite data have approximately the same median photochemical age as the AERONET data. This restriction resulted in a small change of the optimal BC emission estimate, which increased by less than 3 %. This result does not necessarily mean that the BB aerosol composition and its optical properties are not strongly affected by aging; it may actually mean that changes of AOD and AAOD, as well as those of the monthly BC emission estimates due to aerosol aging, tend to compensate each other in the total BC emission estimate.
To get an idea about such a bias, we followed the approach suggested by  Konovalov et al. (2014). Specifically, we first selected the days and grid cells (irrespective of the availability of AAOD data) in which the MODIS-retrieved AOD data are available and the contribution of fires to the modeled AOD values (corresponding to the selected the days and grid cells) does not exceed 10 % of the background AOD values. We then evaluated the mean difference between the MODIS-retrieved and modeled AOD for these selected data points. We found that the mean value for the modeled AOD (∼ 0. 17) is considerably higher than the mean value (∼ 0. 10) for the observed AOD. Taking into account that the bias in the background AOD values in pixels affected by fires may be somewhat different from that representative of background conditions, we considered larger changes in the background AOD by increasing or decreasing it by 50 %.
The test results indicate that a probable positive bias in the background AOD values is associated with some underestimation (by less than 20 %) of BC emissions in our procedure; if the bias were absent, the difference between the BC emission estimates inferred from the satellite observations and those calculated with the GFED4 data would be even larger than in the base case. The sensitivity of the optimal estimate is strongly asymmetric with respect to the enhancement and reduction of the background AOD: this is probably due to an impact of the changes in the background AOD on the selection of data according to the criterion given by Eq. (  8 ). Test case no. 6 addresses the uncertainties associated with the background AAOD. On the one hand, the AAOD data have been retrieved from the OMI measurements under the assumption that each observed pixel is characterized by only one type of aerosol.
However, the overestimation can hardly be very large for the very intense and widespread Siberian fires considered, because, in this case, the smoke plumes are likely to cover a large fraction of the grid cell area. To examine this issue, we disregarded any gridded AAOD data points that comprised less than 10 different AAOD observations (data pixels), while the maximum number of the pixels per grid cell in the data considered equals 26. Contrary to our expectations, we found that the estimate obtained in test case no. 10 is larger (by 17 %). This increase is found to be mostly due to an increase in the optimal estimates of F OC. Apparently, the above limitation resulted in the selection of MODIS AOD data that are more representative of grid cells affected by major fires and are matched by smaller AOD values simulated for the base case.
Therefore, the result of this test is not indicative of any representativeness issue for the available OMI retrievals. In general, the results presented in this section demonstrate that our estimate of the total BC emissions from Siberian fires is sufficiently robust with respect to possible uncertainties in the input data and the choices made in the estimation procedure. In particular, these results strongly support our findings that the GFED4 inventory significantly underestimates the BC emissions from Siberian fires.
Conclusions We have investigated the feasibility of constraining BC emissions from open biomass burning with AAOD retrievals from OMI satellite measurements by considering the case of the severe fires that occurred in Siberia in 2012. We developed an inverse modeling procedure enabling the optimization of BB emissions based on MODIS FRP measurements by combining OMI AAOD retrievals and MODIS AOD data with simulations performed using the CHIMERE CTM. To limit possible errors in the simulated AAOD data due to uncertainties in the absorption properties of the BB aerosol, we employed an empirical parameterization predicting AAOD as a function of AOD and the ratio of BC and OC column densities. The parameterization is based on the experimental findings reported earlier  (Pokhrel et al. , 2016)  and is fitted to data from two AERONET sites in Siberia; it assumes that the SSA of BB aerosol particles is a linear function of the elemental to total carbon ratio.
As a result of the application of our inverse modeling procedure to the measurement and simulation data characterizing the BB aerosol in Siberia during the period from 1 May to 30 September, we evaluated the monthly correction factors for BB BC and OC emissions calculated using the FRP data and obtained top-down estimates of the total BC and OC amounts emitted each month in the period considered. Note that our estimation method implies that the BC emissions are evaluated as emissions of elemental carbon (EC) measured using a thermo-optical technique. To validate the optimized BC and OC emissions, we used them to perform simulations that were evaluated against independent observational data. Specifically, we first compared our simulations with the OMI AAOD and MODIS AOD data that had been withheld from the optimization procedure.
The slopes of linear fits to the BC and PM 2. 5 data from the simulations and observations are found to be in good agreement (within 10 %). This finding further confirms that the BB aerosol composition was simulated adequately. We found that Siberian fires emitted 405 ± 135 Gg of BC in the period from May to September 2012 (at the 90 % confidence level). The BB BC emissions were largest in July, when 139±49 Tg of BC was emitted and smallest in September (20 ± 9 Gg). Our estimates were compared to the corresponding estimates obtained from the GFED4 and FEI-NE databases. Our estimate of the total BB BC emissions in the study region and period is found to be a factor of 2 larger than the GFED4 estimate, but a factor of 1. 5 smaller than the FEI-NE estimate. The differences of our monthly and season total BC emission estimates with respect to both GFED4 and www.
atmos-chem-phys. net/18/14889/2018/ Atmos. Chem. Phys. , 18, 14889-14924, 2018 FEI-NE data are statistically significant, although the differences with respect to the FEI-NE estimates are smaller than the large uncertainty range reported for the FEI-NE data. The results of several sensitivity tests indicate that, although our estimates can be influenced to some extent by a number of factors associated, in particular, with data selection criteria and uncertainties in the simulations of optical properties of aerosol in the absence of fires, the possible bias in our estimate of the total BC emission is unlikely to exceed the estimated uncertainty of about 35 %. In spite of the significant differences between our BC emission estimates and the GFED data, the ratio of the total BC and OC emission estimates derived from the satellite data (0.
046 ± 0. 014 g g -1 ) is found to be consistent with the ratio of the corresponding BC and OC emission totals according to the GFED data (0. 054 g g -1 ). However, there are considerable differences between the BC/OC emission ratios obtained in this study and those calculated using the GFED4 data for the different months. In particular, a larger value of the ratio of BC and OC emissions in May is found in this study (0. 093 ± 0. 030 g g -1 ) compared to that suggested by GFED4 (0. 06 g g -1 ): this difference may be indicative of an underestimation of BC emissions from agricultural burns and grass fires in the GFED4 inventory. Finally, we estimated that about a quarter of the huge BC amount emitted from Siberian fires in the period from May to September 2012 was transported across the polar circle into the Arctic.
Therefore, the results of this study have a direct implication for reducing major uncertainties associated with the current estimates of sources of BC in the atmosphere and snow/ice cover in the Arctic and for improving the general understanding of the role of BC in the Arctic climate system. Overall, our analysis demonstrated that the OMI AAOD retrievals combined with the MODIS AOD data can provide useful constraints to the BB BC emissions. It is especially noteworthy that in the case considered in this study, the entire uncertainty range for the BC emission estimates constrained with the satellite measurements turned out to be a factor of 1. 5 smaller than the difference between the corresponding estimates provided by the two state-of-the-art emission inventories, GFED4 and FEI-NE. A major factor limiting the accuracy of the top-down estimates of BC emissions from Siberian fires is the uncertainty of the AAOD simulations.
To reduce this uncertainty, more data from remote sensing and in situ measurements of aerosol optical properties and composition (such as measurements of SSA and of the BC/OC and OC/POM ratios) in northern Eurasia are needed. Another significant uncertainty source in our estimates is associated with the estimation of the altitude of the aerosol layer center of mass. Accordingly, future developments of our approach should include an evaluation and optimization of the simulated vertical distribution of BB aerosol using suitable satellite observations, such as, e. g. , Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)  (Vaughan et al. , 2004). Data availability. The OMAERUV dataset is available from the NASA Goddard Earth Sciences Data and Information Services Center  (Torres, 2006 ; https://disc.
sci. gsfc. nasa. gov/datasets/ OMAERUV_V003/summary; last access: 12 April 2018). The MYD04-L2 dataset  (Levy and Hsu, 2015)  and the MYD14/MOD14 datasets  (Giglio and Justice, 2015a, b)  are available from the Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC) and from the NASA EOS-DIS Land Processes Distributed Active Archive Center (LP DAAC), respectively, through the NASA Earth Data Search (https://search. earthdata. nasa. gov/, last access: 26 April 2018). The aerosol measurement data from the ZOTTO site can be made available upon request from Eugene F. Mikhailov (eugene. mikhailov@spbu. ru. ). Access to the aircraft measurement data used in this study is organized on the YAK-AEROSIB project website: https://yak-aerosib. lsce. ipsl. fr/, last access: 14 October 2018.
(2009). The Q24N mutation (replacement of the cag codon into aac) was incorporated to the construct with the SLIM method. Sequences of applied primers are listed in Supplementary Table  1 (RgpAQ24N section). This plasmid was introduced into the P. gingivalis W83 RgpB strain lacking the whole rgpB gene by the electroporation and the recombined clones were selected with 1 µg/ml of tetracycline. The resulting strain was partially sequenced and named RgpBdel/RgpAQ24N. The non-mutated master plasmid was also introduced into the RgpB strain P. gingivalis W83 and the unaffected expression and activity of RgpA was observed (data not shown). For Kgp mutagenesis, the pNKgp-cep master plasmid was created in a similar manner. First, two fragments adjacent to the start of the hypothetical Kgp promotor were amplified from the genomic DNA, the 809 bp upstream fragment with Kg_Up_F and Kg_Up_R primers, while the 3271 bp downstream fragment with Kg_Dw_F and Kg_Dw_R primers.
The beta-lactamase gene cepA was amplified with primers CepA_F and CepA_R from template synthetized by the Life Technologies based on the sequence deposited under AAA21538. 1 number (Gene Bank). The pUC19 plasmid was linearized with primers pUC_SphI_R and pUC_BamHI_F. The Q20N mutation (replacement of the caa codon by aat) was incorporated to the construct by the SLIM method. Sequences of used primers are listed in Supplementary Table 1 (KgpQ20N section). This plasmid was introduced into the wild type P. gingivalis W83 by the electroporation and the recombined clones were selected with 2 µg/ml of ampicillin. Obtained strain was partially sequenced and named KgpQ20N. As a control, the non-mutated master plasmid was also electroporated into the P. gingivalis W83 strain and the unaffected expression and activity of Kgp was observed (data not shown).
The presence of 0. 1% Sarkosyl detergent in the assay did not affect the rate of substrate hydrolysis as determined with purified RgpB (data not shown). The rate of formation of p-nitroanilide was measured at 405 nm using a SpectraMax Plus spectrophotometer (Molecular Devices Inc. , San Jose, CA, United States). For ease of comparison between mutants and statistical analyses of independent repetitions, activity units were defined as the total activity present in the RgpB + control mutant culture equaling 100 U for culture partitioning studies, the total activity in the RgpB + control mutant cells equaling 100 U for cellular fractionation studies, or the total activity in the RgpB + control mutant membranes equaling 100 U for membrane fractionation studies.
gingivalis in late exponential/early stationary phase of growth was fractionated into cytoplasm and periplasm (CP), total membranes (M), outer membrane (OM), and inner membrane (IM). The purity of the membrane fractions was verified by the exclusive presence of the biotincontaining 15-kDa biotin carboxyl carrier protein (AccA alias MmdC or PG1609) and gingipains in the IM and OM, respectively  (Veith et al. , 2014)  (data not shown). QC activity of the fractions was then measured using the enzymecoupled assay already used previously to demonstrate the activity of the recombinant enzyme. QC activity was found in the IM and in fractions containing IM (CE and M) but not CP and OM (Figure  1A ) clearly indicating that PgQC is anchored in the inner membrane. This localization was further confirmed by Western blot analysis of enriched subcellular fractions using rabbit polyclonal antibodies anti PgQC (Figure  1B ).
Altogether 27 proteins, all putative SPI substrates, with N-terminal pyroglutamate were identified (Table  1 , last row, three proteins with pGlu and ambiguous location are omitted from the table). Interestingly, no semi-tryptic peptides with N-terminal glutamine were found in the entire P. gingivalis dataset, suggesting widespread pyroglutamate formation (Table  1  and Supplementary Data Sheet 2). In order to further confirm this conclusion, we compared sequences around the cyclization site (and thus the SPI cleavage site) for proteins that were experimentally identified, had a glutamine after the predicted SPI cleavage site, and for which evidence for pyroglutamate formation was either available or not. The region upstream of the SPI cleavage site, normally not expected to influence QC, was included in the comparison in case SPI and QC may act together and QC preferences may be influenced by SPI preferences.
Mutation of the RgpA, RgpB, or Kgp glutamine after the SPI cleavage site did not alter P. gingivalis growth or the extracellular activity of prolyl tripeptidyl peptidase secreted by P. gingivalis independent of T9SS (data not shown). Gingipain activity was assayed in full cultures and the cell-free culture medium from cultures grown to the mid-exponential (OD 600 nm = 0. 6-0. 8), late exponential/early stationary (OD 600 nm = 1. 2-1. 4) and stationary (OD 600 nm > 2. 0) phase of growth. We assayed either total extracellular activity, or separately the activities associated with the outer membrane surface and with the culture medium. In all cases, activities increased strongly over time from midexponential to late stationary cultures. Surprisingly, mutation of the Q after the SPI cleavage site had variable effects on the different gingipains.
Bacteroidetes Have Orthologs of Animal and Plant QCs We searched complete bacterial proteomes in UNIPROT for orthologs of animal-and plant-type QCs. In a first step, we used the prototypical human and Arabidopsis thaliana QC sequences as queries. In a set of 1878 proteomes, we found 602 animal-type QCs, among them 402 (67%) in Bacteroidetes. We also identified 991 plant-type QCs, among them 401 (40%) in Bacteroidetes. As Bacteroidetes account for less than 10% of the proteome data (and even less in the redundant set), it is clear that QCs, particularly of the animal-type, are enriched in the Bacteroidetes. Orthologues of animal-and plant-type QCs tended to segregate according to phylogeny. Animal-type QCs were typically found in Bacteroidia, plant-type QCs in Flavobacteriia. As the number of candidate QCs was smaller than the number of proteomes, we attempted to enlarge the set of candidate QCs by carrying out BLASTP queries with representative sequences from Bacteroidia and Flavobacteriia, the two largest groups within FIGURE 4 | Q-values averages and Q-value distributions for different groups of bacteria.
thaliana QC. the Bacteroidetes. Starting from these sequences, and correcting for species duplicates, we identified 574 Bacteroidetes species containing animal-type and 507 Bacteroidetes species containing plant-type QC enzymes, but only 63 species containing both types of enzymes (E-value threshold 1E-4), compared to 1540 species in the duplication corrected proteome dataset. We also attempted iterated searches, using representatives of CD-HIT identified sequence clusters  (Makarova et al. , 2006)  to initiate additional searches. With this procedure, still more putative QCs were identified, but the concentration of hits in the Bacteroidetes phylum was reduced, likely because the set of putative QCs became contaminated by peptidases. Despite this complication, we can conclude from the simpler BLASTP searches that most and perhaps even all Bacteroidetes species have enzymes that could be suitable for glutamine cyclization.
Proteomic Datasets Confirm Glutamine Cyclization in Several Bacteroidetes Species In order to confirm widespread pyroglutamyl formation in Bacteroidetes, and not only P. gingivalis, we analyzed additional data from previously reported proteomic studies  (Veith et al. , 2002 (Veith et al. , , 2009 (Veith et al. , , 2013 (Veith et al. , , 2014 (Veith et al. , , 2015)). In addition to the already discussed 27 proteins from P. gingivalis, the collated data identify 27 proteins in Tannerella forsythia, 13 in Parabacteroides distasonis, 8 in Prevotella intermedia and 7 in Cytophaga hutchinsonii (Supplementary Figure  4  and Supplementary Data Sheet 2) with N-terminal pyroglutamate residue. N-terminal residues other than pyroglutamate were rare, as predicted from the bioinformatic studies. Pyroglutamate was not detected at the amino-terminus of all SPI substrates that are predicted to expose an N-terminal glutamine residue after SPI cleavage (Table  1 ), most likely due to incomplete coverage and not due to selective pyroglutamate formation.
Strikingly, these isolates showed a high frequency of homozygosity at the genomic region controlling fungal compatibility (also called the mating-type locus in fungi, 12/21 isolates, 57%), which is in contrast with what was previously reported (110/1294 strains, 8. 5%  12  ). This may reflect antifungal exposure of these clinical isolates, which also likely explains their high frequency of aneuploidies  18. In this work, we sequenced the genomes of 182 C. albicans isolates collected worldwide, an order of magnitude more isolates than has been considered previously in population genomic studies of C. albicans. Our dataset contains commensal isolates, as well as ones responsible for superficial and invasive infections, and also includes the previously sequenced laboratory strain SC5314  19  and representatives from all major clusters previously defined by MLST  12, 13, 15.
2%) showed a homozygous mating-type locus. Phenotypic diversity in C. albicans can arise rapidly through LOH, spanning whole chromosomes or shorter contiguous chromosome segments  18, 22. We detected numerous LOH events across our 182 isolates. Some were ancient events that had arisen before cluster expansion (Fig. 1 , examples highlighted by black dotted boxes) and others were more recent and strain specific (Fig. 1 , horizontal white stripes specific to a single strain). Long range LOH events were predominantly the consequence of mitotic crossovers or break-induced replication events while events of whole chromosome loss were rare (Fig. 1 ). Strains belonging to clade 13 showed a unique pattern with lower heterozygosity (Fig. 1  and see below). Analysis of genome-wide variation revealed that each of the 182 isolates on average contain 65,629 heterozygous SNPs (1 heterozygous SNP every 204 bp, Supplementary Data 1) and 14,189 heterozygous insertiondeletion events (indels), which is in agreement with previous genomic analysis  17.