Molecular genotyping of bacillus anthracis strains from Georgia and northeastern part of Turkey

Bacillus anthracis is the causal agent of anthrax and has a history of use as a biological weapon. Anthrax cases occur worldwide and the disease is endemic in certain regions. Here we describe a study of the genetic diversity of B. anthracis strains in two endemic areas: The country of Georgia and the Kars region of Turkey. Thirty Turkish isolates and thirty Georgian isolates were subjected to Single Nucleotide Polymorphism (SNP) sub typing, followed by higher-resolution genotyping using 25-loci variable-number tandem repeat analysis (MLVA-25). Canonical SNP typing indicated that Turkish strains belonged to both the A.Br.003 linage and the Australian 94 lineage. In light of a recent analysis that placed the majority of Georgian B. anthracis isolates in one phylogenetic group, we screened the Turkish strains using a previously developed Georgian SNP panel. Minimal diversity was observed among the Kars strains within the Georgian SNP lineage: all 30 of these strains grouped with A.Br.026, ten strains were derived from A.Br.028, and only two isolates belonged to A.Br.029. According to the results of MLVA-25 genotyping, all 30 Turkish strains belong to two clusters. Cluster A is more diverse than cluster B. Our results suggest that B. anthracis strains originating from Georgia and the northeastern part of Turkey are genetically interrelated, which could be explained by the geographic proximity of the countries

Molecular genotyping of bacillus anthracis strains from Georgia and northeastern part of Turkey

Bacillus anthracis is the causal agent of anthrax and has a history of use as a biological weapon. Anthrax cases occur worldwide and the disease is endemic in certain regions. Here we describe a study of the genetic diversity of B. anthracis strains in two endemic areas: The country of Georgia and the Kars region of Turkey. Thirty Turkish isolates and thirty Georgian isolates were subjected to Single Nucleotide Polymorphism (SNP) sub typing, followed by higher-resolution genotyping using 25-loci variable-number tandem repeat analysis (MLVA-25). Canonical SNP typing indicated that Turkish strains belonged to both the A.Br.003 linage and the Australian 94 lineage. In light of a recent analysis that placed the majority of Georgian B. anthracis isolates in one phylogenetic group, we screened the Turkish strains using a previously developed Georgian SNP panel. Minimal diversity was observed among the Kars strains within the Georgian SNP lineage: all 30 of these strains grouped with A.Br.026, ten strains were derived from A.Br.028, and only two isolates belonged to A.Br.029. According to the results of MLVA-25 genotyping, all 30 Turkish strains belong to two clusters. Cluster A is more diverse than cluster B. Our results suggest that B. anthracis strains originating from Georgia and the northeastern part of Turkey are genetically interrelated, which could be explained by the geographic proximity of the countries

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.</p

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission